Evidence for geographic variation in the diets of late Pleistocene and early Holocene<i>Bison</i>in North America, and differences from the diets of recent<i>Bison</i>
Bibliographic record
Abstract
Abstract During the late Pleistocene and early Holocene, Bisonwas widely dispersed across North America and occupied most regions not covered by ice sheets. A dietary study onBisonpaleopopulations from Alaska, New Mexico, Florida, and Texas was performed using two methods that relate dental wear patterns to diet, mesowear analysis and microwear analysis. These data were compared to a mixed sample of extantBisonfrom the North American central plains, extant woodBisonfrom Alberta (Canada) and a variety of other modern ungulates. Mesowear relates macroscopic molar facet shape to levels of dietary abrasion. The mesowear signature observed on fossilBisondiffers significantly from the hyper-abrasive grazing diet of extantBison. Tooth microwear examines wear on the surface of enamel at a microscopic scale. The microwear signal of fossil samples resembles to modernBison, but the fossil samples show a greater diversity of features, suggesting that fossilBisonpopulations regularly consumed food items that are texturally inconsistent with the short-grass diet typical of modern plainsBison. Mesowear and microwear signals of fossilBisonsamples most closely resemble a variety of typical mixed feeding ungulates, all with diets that are substantially less abrasive than what is typical for modern plainsBison. Furthermore, statistical tests suggest significant differences between the microwear signatures of the fossil samples, thus revealing geographic variability in PleistoceneBisondiets. This study reveals that fossils are of value in developing an understanding of the dietary breadth and ecological versatility of species that, in recent times, are rare, endangered, and occupy only a small remnant of their former ranges.
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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 | 0.000 |
| 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) | 0.002 | 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".