Data from: Tying the knot between morphology and development: Using the patterning cascade model between cheek teeth to study the evolution of molarization in hoofed mammals
Bibliographic record
Abstract
Hoofed mammal premolars show a range of occlusal crown morphology from molariform to caniform – the placement of taxa on this spectrum can be described as the relative molarization of the premolars. Molarized premolars function together with the molars in grinding mastication in most of the lineages in which these unique premolars appear. The degree of molarization varies across dietary ecologies, which has led to cheek tooth morphology being designated as an important contributor to dietary predictions in extant and extinct taxa. Recent research into mammalian occlusal cheek tooth patterning have found independent patterning mechanisms of the premolars and molars. A research gap exists in understanding how molarization of the premolars has occurred so frequently in hoofed mammals if these dental regions are independent in their patterning. In this study, we tested the application of the patterning cascade model to the lower premolar-molar boundary in a geometric morphometrics framework in hoofed mammals. We used 2D geometric morphometrics to study occlusal cuspid covariation at the lower p4-m1 boundaries of 16 artiodactyl and 18 perissodactyl species. Phylogenetically informed modularity analyses were used to test alternate a priori hypotheses originating from evolutionary, developmental, and functional considerations of cheek tooth morphogenesis. Our results showed artiodactyls and perissodactyls differ significantly in their p4-m1 boundary covariation patterns, which we hypothesize could be caused by heterochronic shifts between premolar and molar development. To our knowledge, our study is the first to contribute a comprehensive yet accesible 2D geometric morphometric method to further investigate the evolution of molarized premolars.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".