The variation of angles between anterior and posterior carinae of tyrannosaurid teeth
Bibliographic record
Abstract
Tyrannosaurid tooth measurements have been shown to be a powerful tool for systematic analyses, as well as for studies on function and evolution of theropod dentition. In this analysis, a variable not previously addressed in depth is added to the tyrannosaurid data set. The angle between the anterior and posterior carinae can be difficult to measure consistently and a method is hereby proposed through the use of a digitizer. Five tyrannosaurid genera were analyzed: Tyrannosaurus , Tarbosaurus , Albertosaurus , Daspletosaurus , and Gorgosaurus . Only in situ data were used, and therefore some of the taxa had a limited amount of information available for this analysis. The measurements were analyzed through multivariate analyses using Paleontological Statistics (PAST), version 2.06. The analyses included principal component analyses (PCAs), discriminant analyses (DAs), and canonical variates analyses (CVAs). The results of these analyses revealed that the angle between carinae contributes significantly to the variation in the tyrannosaurid tooth data set. Additionally, this variable showed a strong correlation to tooth function (and, consequently, to tooth families), rather than tooth size. The variation observed between taxa at this stage seems insufficient for systematic purposes, however additional in situ data would help improve the effectiveness of this tool.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".