An Analysis of North American Taeniolabidoid Multituberculate (Mammalia, Allotheria) Dentitions Using Mammalian Dietary Proxies
Bibliographic record
Abstract
In this thesis, a set of dietary proxies – dental microwear analysis, cusp row ratios (CRR) (similar to shearing ratios), relief index (RFI), orientation patch count rotated (OPCR), and Dirichlet normal energy (DNE) – was used to infer diets of North American taeniolabidoid multituberculates. Based on the signals recovered by these proxies, taeniolabidoid diets did not vary consistently with body size: small-bodied and large-bodied taeniolabidoids had similar dietary signals for almost all proxies, the only difference being in microwear feature dimensions. Dental microwear signals suggest that taeniolabidoids and non-taeniolabidoid cimolodontans may have had different diets, but all other proxies have recovered equivalent signals between the two groups. Dietary classifications are inconsistent among CRR, RFI, OPCR, and DNE. This suggests that these proxies are not equally good predictors and that their generalizability to non-therian mammals may need to be re-evaluated.
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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) | 0.001 | 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 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".