Body size, sexual dimorphism, and seasonal mass fluctuations in a larger sika deer subspecies, the Hokkaido sika deer (<i>Cervus nippon yesoensis</i> Heude, 1884)
Bibliographic record
Abstract
Measurements of shoulder height, body length, hind-foot length, and total body mass were collected from 309 Hokkaido sika deer (Cervus nippon yesoensis Heude, 1884) (115 males and 194 females) and analyzed statistically for sexual dimorphism and seasonal body mass fluctuations. The von Bertalanffy equation was fitted to the growth curves that resulted. Asymptotic shoulder height, body length, and hind-foot length were 106.2, 112.6, and 52.9 cm in males and 94.8, 103.9, and 49.4 cm in females, respectively. Total body mass showed distinct seasonal fluctuations, ranging between 102.8 and 151.0 kg in adult males and 68.0 and 99.8 kg in adult females. Male/female ratios in shoulder height, body length, hind-foot length, and total mass were 1.12, 1.08, 1.07, and 1.51, respectively. These results indicate that the Hokkaido sika deer is one of the largest subspecies, at least in skeleton size. A larger body and longer hind foot would seem to be evolutionary adaptations to Hokkaido's cold, snowy environment.
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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 | 0.000 |
| 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) | 0.001 | 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".