node support efficacy in congreve & lamsdell matrices0.2 trees1–10 0 0 0 385 385 385 770 770...

53
Node support efficacy in Congreve & Lamsdell matrices Martin R. Smith [email protected] 2020-01-20 Contents 0.1 Summary ............................................... 2 0.2 Trees 1–10 ............................................... 3 0.3 Trees 11–20 .............................................. 8 0.4 Trees 21–30 .............................................. 13 0.5 Trees 31–40 .............................................. 18 0.6 Trees 41–50 .............................................. 23 0.7 Trees 51–60 .............................................. 28 0.8 Trees 61–70 .............................................. 33 0.9 Trees 71–80 .............................................. 38 0.10 Trees 81–90 .............................................. 43 0.11 Trees 91–100 ............................................. 48 References .................................................. 53 This page depicts the analytical results of all 100 matrices generated by Congreve & Lamsdell [1] using a ternary plotting approach [2], with quartets and partitions used as distance metrics. The most highly resolved tree is progressively reduced by collapsing nodes with a support value below an increasing threshold. 1

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Page 1: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

Node support efficacy in Congreve & Lamsdell matrices

Martin R. Smith [email protected]

2020-01-20

Contents0.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.2 Trees 1–10 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30.3 Trees 11–20 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80.4 Trees 21–30 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130.5 Trees 31–40 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180.6 Trees 41–50 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230.7 Trees 51–60 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 280.8 Trees 61–70 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330.9 Trees 71–80 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 380.10 Trees 81–90 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 430.11 Trees 91–100 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

This page depicts the analytical results of all 100 matrices generated by Congreve & Lamsdell [1] using aternary plotting approach [2], with quartets and partitions used as distance metrics.

The most highly resolved tree is progressively reduced by collapsing nodes with a support value below anincreasing threshold.

1

Page 2: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0.1 Summary

0

0

0

385

385

385

770

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1155

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1540

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1925

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All datasets (averaged). Equal weights. 0

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MarkovBremerBootFreqBoot GCJack FreqJack GC

Though the Bootstrap GC metric systematically produces the lowest normalized tree distances (SD/MaxI), itis not significantly better than other methods. The following table reports P values that fail to reject the nullhypothesis that the specified node support metric is equally good at ascribing incorrect nodes the lowestsupport values.

eq k1 k2 k3 k5 kX kCBootstrap GC 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000Bootstrap Freq 0.9840650 0.9915189 0.9934145 0.9760370 0.9485781 0.9615921 0.9720185Jackknife GC 0.9888177 0.9995312 0.9331647 0.9599348 0.9637166 0.9268107 0.9743023Jackknife Freq 0.9942934 0.9554285 0.9509308 0.9839102 0.8639063 0.9408796 0.9723566Bremer 0.4347916 0.3324499 0.5075762 0.4474386 0.3405988 0.2397081 0.8365157

2

Page 3: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0.2 Trees 1–10

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

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1925

1925

1925

2310

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2695

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Dataset 1: CI=0.28. Equal weights 0

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1

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22

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33

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44

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PartitionsIncreasing R

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MarkovBremerBootFreqBoot GCJack FreqJack GC

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2695

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3080

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Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

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770

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11551155

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Dataset 2: CI=0.25. Equal weights 0

0

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66

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Increasing RF

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0

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385

385

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770

770

770

1155

11551155

1540

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1925

1925

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2310

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2695

3080

3080

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tical

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Implied weights (k = 3) 0

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Increasing RF

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MarkovBremerBootFreqBoot GCJack FreqJack GC

3

Page 4: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

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0

385

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770

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1155

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1540

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Decreasing resolution Increasing divergence

Dataset 3: CI=0.29. Equal weights 0

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Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

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770

1155

11551155

1540

1540

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19251925

1925

2310

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2695

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3080

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3465

3465

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tical

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Decreasing resolution Increasing divergence

Dataset 4: CI=0.29. Equal weights 0

0

0

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66

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

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385

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385

770

770

770

1155

11551155

1540

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1925

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2310

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2695

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3080

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Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

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Partitions

Increasing RF

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MarkovBremerBootFreqBoot GCJack FreqJack GC

4

Page 5: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

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385

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770

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1155

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1540

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1925

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Decreasing resolution Increasing divergence

Dataset 5: CI=0.26. Equal weights 0

0

0

1

1

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55

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66

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0

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385

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770

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1155

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1540

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2695

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3080

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3465

3465

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different quarte

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tical

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Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

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different partiti

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

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0385

385

385

770

770

770

1155

11551155

1540

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19251925

1925

2310

2310

2310

2695

2695

2695

3080

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3465

3465

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3850

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tical

qua

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Quartets

Decreasing resolution Increasing divergence

Dataset 6: CI=0.26. Equal weights 0

0

0

1

1

1

2

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66

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

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3850

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different quarte

ts

iden

tical

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Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

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66

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Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

5

Page 6: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

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1925

1925

1925

2310

2310

2310

2695

2695

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3080

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3080

3465

3465

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3850

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Decreasing resolution Increasing divergence

Dataset 7: CI=0.27. Equal weights 0

0

0

1

1

1

2

2

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3

3

3

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55

5

66

6

77

78

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89

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19 unresolved partitions

different partiti

onsiden

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

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66

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19 unresolved partitions

different partiti

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

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tical

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Quartets

Decreasing resolution Increasing divergence

Dataset 8: CI=0.25. Equal weights 0

0

0

1

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4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

6

Page 7: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 9: CI=0.24. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 10: CI=0.29. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

7

Page 8: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0.3 Trees 11–20

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 11: CI=0.25. Equal weights 0

0

0

1

1

1

22

2

33

3

44

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

PartitionsIncreasing R

F distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

11551155

1155

1540

1540

1540

1925

1925

19252310

2310

23102695

2695

26953080

3080

30803465

3465

34653850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 12: CI=0.29. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

nsPartitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

8

Page 9: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 13: CI=0.25. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 14: CI=0.25. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

9

Page 10: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 15: CI=0.25. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 16: CI=0.25. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

10

Page 11: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 17: CI=0.27. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 18: CI=0.28. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

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16

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19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

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19 unresolved partitions

different partiti

onsiden

tical

par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

11

Page 12: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

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sQuartets

Decreasing resolution Increasing divergence

Dataset 19: CI=0.3. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

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14

14 15

15

1516

16

1617

17

1718

18

1819

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19 unresolved partitions

different partiti

onsiden

tical

par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 20: CI=0.25. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

12

Page 13: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0.4 Trees 21–30

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 21: CI=0.26. Equal weights 0

0

0

1

1

1

22

2

33

3

44

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

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16

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19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

PartitionsIncreasing R

F distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

11551155

1155

1540

1540

1540

1925

1925

19252310

2310

23102695

2695

26953080

3080

30803465

3465

34653850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 22: CI=0.26. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

nsPartitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

tical

par

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ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

13

Page 14: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 23: CI=0.25. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 24: CI=0.23. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

tical

par

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ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

14

Page 15: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 25: CI=0.28. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 26: CI=0.27. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

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par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

15

Page 16: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 27: CI=0.26. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 28: CI=0.27. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

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16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

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17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

tical

par

titio

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

16

Page 17: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 29: CI=0.29. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 30: CI=0.25. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

17

Page 18: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0.5 Trees 31–40

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 31: CI=0.26. Equal weights 0

0

0

1

1

1

22

2

33

3

44

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

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16

17

17

17

18

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18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

PartitionsIncreasing R

F distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

11551155

1155

1540

1540

1540

1925

1925

19252310

2310

23102695

2695

26953080

3080

30803465

3465

34653850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 32: CI=0.25. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

nsPartitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

tical

par

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ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

18

Page 19: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 33: CI=0.27. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 34: CI=0.29. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

tical

par

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ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

19

Page 20: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 35: CI=0.25. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 36: CI=0.24. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

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par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

20

Page 21: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 37: CI=0.26. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 38: CI=0.29. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

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17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

tical

par

titio

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

21

Page 22: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 39: CI=0.25. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

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14 15

15

1516

16

1617

17

1718

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1819

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19 unresolved partitions

different partiti

onsiden

tical

par

titio

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 40: CI=0.24. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

22

Page 23: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0.6 Trees 41–50

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 41: CI=0.3. Equal weights 0

0

0

1

1

1

22

2

33

3

44

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

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16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

PartitionsIncreasing R

F distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

11551155

1155

1540

1540

1540

1925

1925

19252310

2310

23102695

2695

26953080

3080

30803465

3465

34653850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 42: CI=0.24. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

nsPartitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

23

Page 24: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 43: CI=0.27. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 44: CI=0.27. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

24

Page 25: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 45: CI=0.27. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 46: CI=0.24. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

tical

par

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ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

25

Page 26: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 47: CI=0.29. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 48: CI=0.27. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

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different partiti

onsiden

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par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

26

Page 27: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 49: CI=0.28. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 50: CI=0.25. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

27

Page 28: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0.7 Trees 51–60

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 51: CI=0.3. Equal weights 0

0

0

1

1

1

22

2

33

3

44

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

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16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

PartitionsIncreasing R

F distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

11551155

1155

1540

1540

1540

1925

1925

19252310

2310

23102695

2695

26953080

3080

30803465

3465

34653850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 52: CI=0.25. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

nsPartitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

28

Page 29: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 53: CI=0.25. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 54: CI=0.28. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

29

Page 30: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 55: CI=0.28. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 56: CI=0.31. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

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par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

30

Page 31: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 57: CI=0.25. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 58: CI=0.25. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

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9

10

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11

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11

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12

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different partiti

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Partitions

Increasing RF

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MarkovBremerBootFreqBoot GCJack FreqJack GC

31

Page 32: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

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3080

3465

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different quarte

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iden

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Decreasing resolution Increasing divergence

Dataset 59: CI=0.26. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

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8

89

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910

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

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0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

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13

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14

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14 15

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19 unresolved partitions

different partiti

onsiden

tical

par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 60: CI=0.24. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

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14 15

15

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19 unresolved partitions

different partiti

onsiden

tical

par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

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Partitions

Increasing RF

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MarkovBremerBootFreqBoot GCJack FreqJack GC

32

Page 33: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0.8 Trees 61–70

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

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s

Quartets

Decreasing resolution Increasing divergence

Dataset 61: CI=0.26. Equal weights 0

0

0

1

1

1

22

2

33

3

44

4

5

5

5

6

66

7

77

8

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19 unresolved partitions

different partiti

onsiden

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par

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PartitionsIncreasing R

F distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

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17

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19 unresolved partitions

different partiti

onsiden

tical

par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

11551155

1155

1540

1540

1540

1925

1925

19252310

2310

23102695

2695

26953080

3080

30803465

3465

34653850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 62: CI=0.26. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

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14 15

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19 unresolved partitions

different partiti

onsiden

tical

par

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nsPartitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

33

Page 34: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

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sQuartets

Decreasing resolution Increasing divergence

Dataset 63: CI=0.24. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

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1112

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1213

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14 15

15

1516

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1617

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1718

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1819

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19 unresolved partitions

different partiti

onsiden

tical

par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 64: CI=0.29. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

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18

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19 unresolved partitions

different partiti

onsiden

tical

par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

34

Page 35: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 65: CI=0.25. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

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ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

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ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 66: CI=0.27. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

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16

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19 unresolved partitions

different partiti

onsiden

tical

par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

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Partitions

Increasing RF

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MarkovBremerBootFreqBoot GCJack FreqJack GC

35

Page 36: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

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sQuartets

Decreasing resolution Increasing divergence

Dataset 67: CI=0.26. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

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ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

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s

Quartets

Decreasing resolution Increasing divergence

Dataset 68: CI=0.31. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

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19 unresolved partitions

different partiti

onsiden

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par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

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19 unresolved partitions

different partiti

onsiden

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par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

36

Page 37: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

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sQuartets

Decreasing resolution Increasing divergence

Dataset 69: CI=0.27. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

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1617

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1819

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19 unresolved partitions

different partiti

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par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

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18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 70: CI=0.27. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

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18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

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17

17

18

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different partiti

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par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

37

Page 38: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0.9 Trees 71–80

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 71: CI=0.27. Equal weights 0

0

0

1

1

1

22

2

33

3

44

4

5

5

5

6

66

7

77

8

8

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9

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10

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11

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14 15

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19 unresolved partitions

different partiti

onsiden

tical

par

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PartitionsIncreasing R

F distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

11551155

1155

1540

1540

1540

1925

1925

19252310

2310

23102695

2695

26953080

3080

30803465

3465

34653850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 72: CI=0.29. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

nsPartitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

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18

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19 unresolved partitions

different partiti

onsiden

tical

par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

38

Page 39: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 73: CI=0.28. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 74: CI=0.28. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

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19 unresolved partitions

different partiti

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

39

Page 40: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 75: CI=0.24. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 76: CI=0.26. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

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16

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

40

Page 41: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 77: CI=0.28. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 78: CI=0.24. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

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17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

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17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

tical

par

titio

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

41

Page 42: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 79: CI=0.24. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

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14 15

15

1516

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1617

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1718

18

1819

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19 unresolved partitions

different partiti

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tical

par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 80: CI=0.27. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

42

Page 43: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0.10 Trees 81–90

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 81: CI=0.27. Equal weights 0

0

0

1

1

1

22

2

33

3

44

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

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19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

PartitionsIncreasing R

F distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

11551155

1155

1540

1540

1540

1925

1925

19252310

2310

23102695

2695

26953080

3080

30803465

3465

34653850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 82: CI=0.28. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

nsPartitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

43

Page 44: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 83: CI=0.25. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 84: CI=0.24. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

44

Page 45: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 85: CI=0.27. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 86: CI=0.27. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

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par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

45

Page 46: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 87: CI=0.23. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 88: CI=0.25. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

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different partiti

onsiden

tical

par

titio

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

46

Page 47: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

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sQuartets

Decreasing resolution Increasing divergence

Dataset 89: CI=0.27. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

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1819

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19 unresolved partitions

different partiti

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par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

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18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 90: CI=0.26. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

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tical

par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

47

Page 48: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0.11 Trees 91–100

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 91: CI=0.26. Equal weights 0

0

0

1

1

1

22

2

33

3

44

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

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19 unresolved partitions

different partiti

onsiden

tical

par

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ns

PartitionsIncreasing R

F distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

11551155

1155

1540

1540

1540

1925

1925

19252310

2310

23102695

2695

26953080

3080

30803465

3465

34653850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 92: CI=0.25. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

nsPartitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

tical

par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

48

Page 49: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 93: CI=0.28. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 94: CI=0.24. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

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19 unresolved partitions

different partiti

onsiden

tical

par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

49

Page 50: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 95: CI=0.24. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 96: CI=0.26. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

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19 unresolved partitions

different partiti

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

50

Page 51: Node support efficacy in Congreve & Lamsdell matrices0.2 Trees1–10 0 0 0 385 385 385 770 770 770 1155 1155 1155 1540 1540 1540 1925 1925 1925 2310 2310 2310 2695 2695 2695 3080 3080

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

sQuartets

Decreasing resolution Increasing divergence

Dataset 97: CI=0.27. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

55

5

66

6

77

78

8

89

9

910

10

1011

11

1112

12

1213

13

1314

14

14 15

15

1516

16

1617

17

1718

18

1819

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0385

385

385

770

770

770

1155

11551155

1540

1540

1540

19251925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

iden

tical

qua

rtet

s

Quartets

Decreasing resolution Increasing divergence

Dataset 98: CI=0.26. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

8

9

9

9

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14 15

15

15

16

16

16

17

17

17

18

18

18

19

19

19 unresolved partitions

different partiti

onsiden

tical

par

titio

ns

Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

385

770

770

770

1155

11551155

1540

1540

1540

1925

1925

1925

2310

2310

2310

2695

2695

2695

3080

3080

3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

ts

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tical

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Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

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3

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4

4

4

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66

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Increasing RF

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MarkovBremerBootFreqBoot GCJack FreqJack GC

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0

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385

385

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770

770

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1155

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1540

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1925

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2310

2310

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2695

2695

2695

3080

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3465

3465

3465

3850

3850

3850 unresolved quartets

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Dataset 99: CI=0.24. Equal weights 0

0

0

1

1

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2

2

3

3

3

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55

5

66

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385

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1925

2310

2310

2310

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2695

2695

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3465

3465

3465

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tical

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Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

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1

2

2

2

3

3

3

4

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5

5

5

6

66

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Increasing RF

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MarkovBremerBootFreqBoot GCJack FreqJack GC

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385

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1540

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1925

2310

2310

2310

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2695

3080

3080

3080

3465

3465

3465

3850

3850

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ts

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tical

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Quartets

Decreasing resolution Increasing divergence

Dataset 100: CI=0.27. Equal weights 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

66

7

77

8

8

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9

9

9

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10

10

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11

12

12

12

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14 15

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18

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18

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tical

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titio

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

0

0

0

385

385

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770

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1540

1540

1540

1925

1925

1925

2310

2310

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2695

2695

2695

3080

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3080

3465

3465

3465

3850

3850

3850 unresolved quartets

different quarte

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tical

qua

rtet

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Quartets

Decreasing resolution Increasing divergence

Implied weights (k = 3) 0

0

0

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

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9

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11

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12

13

13

13

14

14

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15

15

16

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17

17

17

18

18

18

19

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different partiti

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tical

par

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Partitions

Increasing RF

distance

MarkovBremerBootFreqBoot GCJack FreqJack GC

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References

1. Congreve CR, Lamsdell JC. 2016 Implied weighting and its utility in palaeontological datasets: a studyusing modelled phylogenetic matrices. Palaeontology 59, 447–465. (doi:10.1111/pala.12236)

2. Smith MR. 2019 Bayesian and parsimony approaches reconstruct informative trees from simulatedmorphological datasets. Biology Letters 15, 20180632. (doi:10.1098/rsbl.2018.0632)

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