War and Peace in Phylogenetics: A Rejoinder on Total Evidence and Consensus
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
For more than 10 years, systematists have been debating the superiority of character or taxonomic congruence in phylogenetic analysis. In this paper, we demonstrate that the competing approaches can converge to the same solution when a consensus method that accounts for branch lengths is selected. Thus, we propose to use both methods in combination, as a way to corroborate the results of combined and separate analyses. This so-called "global congruence" approach is tested with a wide variety of examples sampled from the literature, and the results are compared with those obtained by standard consensus methods. Our analyses show that when the total evidence and consensus trees differ topologically, collapsing weakly supported nodes with low bootstrap support usually improves "global congruence".
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it