Dental topographic analysis of paromomyid (Plesiadapiformes, Primates) cheek teeth: more than 15 million years of changing surfaces and shifting ecologies
Bibliographic record
Abstract
Plesiadapiforms, appearing near the Cretaceous-Paleogene boundary, represent the first primate radiation and show a diverse array of tooth morphologies. Dental topographic metrics provide quantitative data on occlusal surface shape. We used three metrics, Dirichlet Normal Energy, Relief Index, and 3D Orientation Patch Count Rotated, to assess changes in the morphology of lower fourth premolars and lower second molars in a taxonomically broad sample of one family of plesiadapiforms, Paromomyidae, stretching more than 15 million years. Our results indicate that paromomyids occupied a more diverse range of dietary categories than suspected. Whereas all paromomyids were likely omnivores, some species show higher levels of insectivory, while other taxa are inferred to have been mixed-feeding omnivores with high levels of fruit intake. The results also show that the more primitive members of the different paromomyid lineages were more insectivorous than the derived and more recent members of those lineages. Relief Index values also show taxonomic signals that are consistent with ancestor-descendant relationships hypothesised for species of Phenacolemur. These results suggest that dental topographic metrics are informative to the study of paromomyids for both dietary categorisation and for the distinction of species at a fine taxonomic level.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".