Impact of Methodological Choices on Assessments of the Reliability of Fossil Primate Phylogenetic Hypotheses
Bibliographic record
Abstract
It has been argued in several recent studies that conventional craniodental characters cannot be assumed to be reliable for the purposes of reconstructing primate phylogenetic relationships and that as a consequence little confidence can be invested in published fossil primate phylogenies. Here, we evaluate this claim by revisiting the analyses reported in one of these studies [Collard and Wood, 2000]. Specifically, we investigate whether the use of alternative methodological procedures would have altered their findings. We focus on three key issues: (1) size correction, (2) outgroup composition and (3) non-phylogenetic correlation among characters. Our analyses suggest that the results of Collard and Wood [2000] were not affected by the size correction method they used or by the outgroup they employed. Our analyses also suggest that their results were not affected by their decision to ignore developmental, functional and other non-phylogenetic correlations among the characters in their data sets. Accordingly, our study supports the assertion that conventional craniodental characters cannot be assumed to be reliable for reconstructing primate phylogenetic relationships. This in turn suggests that many published fossil primate phylogenies may be unreliable.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.547 | 0.836 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".