Bibliographic record
Abstract
Heterotachy is a general term to describe positions that evolve at different rates in different lineages. Heterotachy also can generally be viewed as multivariate rates-across-sites variation, which can be described as randomly drawing rates (or branch lengths) from a multivariate distribution for each branch at each site (Wu J, Susko E. 2009. General heterotachy and distance method adjustments. Mol Biol Evol. 26:2689-2697). Motivated by this result, we propose three new distance-based tests: a heterogeneity test, a heterotachy test, and a within-gene heterotachy test and demonstrate with simulations that they perform well under a wide range of conditions. We also applied the first two tests to two real data sets and found that although all these data sets showed significant evidence of heterotachy, there were subtrees for which the data were consistent with an equal rates or rates-across-sites model.heterogeneity, heterotachy, within-gene heterotachy, covarion model, distance method, hypothesis test.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".