Insights into archaeological and modern neotropical biomes: Examining diet and shape variation through white-tailed deer lower third molar
Bibliographic record
Abstract
The white-tailed deer ( Odocoileus virginianus Zimmermann 1780) holds significant ecological importance across the Americas, both historically and in modern times. This species ranges from southern Canada to Brazil and exhibits polytypic characteristics, adapting well to diverse habitats including temperate, subtropical, semi-arid, rainforest, and savanna environments. In paleontology and archaeology, the comparison of dental characteristics between extant mammal species with known diets is commonly employed to infer the feeding behaviors of their ancient counterparts. This method assumes that extant and fossil species share similar dietary preferences, aiding in the identification of past environmental contexts. Consequently, we employed a multiproxy approach, combining the study of dental wear and 2D geometric morphometrics, to investigate potential relationships between molar shape, diet, and biomes among extant white-tailed deer populations across the Americas. Our analysis included a comparison with archaeological data from Panama. We sampled 274 extant lower second molar specimens for micro- and mesowear analysis, along with 105 lower third molar specimens from natural science museums for 2D geometric morphometric analysis. These were compared with a sample of 65 archaeological specimens from Panama. Our findings revealed distinct variations in the shape of lower m3 molars among extant white-tailed deer populations across different biomes, with notable differences observed in the archaeological samples as well. Micro- and mesowear analyses also indicated biome-related differences, suggesting a general browsing diet for white-tailed deer with nuanced variations across biomes. Mesowear analysis further suggested a dietary spectrum ranging from pure browsers to browser-mixed feeders. These findings offer valuable insights for the interpretation of fossil deer specimens recovered from archaeological sites.
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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 | 0.002 |
| 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".