Testing for a predicted decrease in body size in brown bears (<i>Ursus</i> <i>arctos</i>) based on a historical shift in diet
Bibliographic record
Abstract
A recent study found a historical decline in the proportion of meat in the diet of brown bears (Ursus arctos L., 1758) in the Hokkaido Islands, Japan. Because feeding habits are strongly correlated with the body size of animals, the shift in diet should have led to a decrease in the size of these bears. To predict the effects of this dietary shift on the skeletal size in bears, we correlated the femur length in Hokkaido brown bears with the carbon and nitrogen stable isotope values from bone samples and predicted the historical change in their body size. The variation in the femur lengths of the male and female subpopulations was positively correlated with their δ15N values, but not with their δ13C values, and the explanatory power of the constructed model was higher in males than in females. Based on the model and the δ15N values for historic and modern bears, the skeletal size of bear subpopulations in eastern Hokkaido was estimated to have decreased by 10%–18% for males and 8%–9% for females. Our results suggest that a historical dietary shift caused the decrease in the size of the Hokkaido brown bears.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".