On the origin of termite workers: weighing up the phylogenetic evidence
Bibliographic record
Abstract
Resolving the phylogenetic history of a 'true' worker caste in termites is essential to our understanding of termite eusocial evolution. Whether this caste is ancient and monophyletic or derived and polyphyletic will have a tremendous impact on our interpretation of termite eusocial history and remains an outstanding question in termite biology. Recent work has begun to re-examine this question in light of new phylogenetic information, but new questions have now arisen about how best to model character state changes in termite caste systems. In the present paper, we compare the models of Grandcolas and D'Haese [J. Evol. Biol. 15 (2002) 885] and Thompson et al. [J. Evol Biol. 13 (2000) 8691 and attempt to make explicit how these proposals differ with respect to the number of, and homology between, character states. We highlight the support each model has for the two principal, but competing, evolutionary hypotheses outlined above.
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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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".