Stable isotope evidence of meat eating and hunting specialization in adult male chimpanzees
Bibliographic record
Abstract
Observations of hunting and meat eating in our closest living relatives, chimpanzees (Pan troglodytes), suggest that among primates, regular inclusion of meat in the diet is not a characteristic unique to Homo. Wild chimpanzees are known to consume vertebrate meat, but its actual dietary contribution is, depending on the study population, often either unknown or minimal. Constraints on continual direct observation throughout the entire hunting season mean that behavioral observations are limited in their ability to accurately quantify meat consumption. Here we present direct stable isotope evidence supporting behavioral observations of frequent meat eating among wild adult male chimpanzees (Pan troglodytes verus) in Taï National Park, Côte d'Ivoire. Meat eating among some of the male chimpanzees is significant enough to result in a marked isotope signal detectable on a short-term basis in their hair keratin and long-term in their bone collagen. Although both adult males and females and juveniles derive their dietary protein largely from daily fruit and seasonal nut consumption, our data indicate that some adult males also derive a large amount of dietary protein from hunted meat. Our results reinforce behavioral observations of male-dominated hunting and meat eating in adult Taï chimpanzees, suggesting that sex differences in food acquisition and consumption may have persisted throughout hominin evolution, rather than being a recent development in the human lineage.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".