Differential mesowear in the maxillary and mandibular cheek dentition of some ruminants (Artiodactyla)
Bibliographic record
Abstract
The mesowear method assesses the dietary regime of herbivorous mammals based on the attrition/abrasion equilibrium by evaluating cusp shape and relief of upper second molars. The method has recently been extended to include four tooth positions, upper P4-M3, in equids. In this study we determine whether the method can be extended in ruminants by applying it to maxillary and mandibular dentitions of a browser, the giraffe (Giraffa camelopardalis) and two mixed feeders, the oribi (Ourebia ourebi) and the musk ox (Ovibos moschatus). We find that including the upper third molar in addition to the upper second molar provides consistent mesowear classifications in these species. Lower dentitions of mixed feeders score significantly differently in terms of mesowear as compared with upper dentitions. We infer that adaptive optimization in differential anisodonty is related to the composition of the diet and should be mirrored in differential mesowear signals of adjoining upper and lower molars. Our results suggest that in mixed feeders, sharpness is maximized in upper teeth, whereas in specialized feeders this is not the case.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".