Body-condition dynamics in a northern ungulate gaining fat in winter
Bibliographic record
Abstract
Individual condition generally depends on density and is partly determined by habitat quality and climate. We studied long-term trends in the condition and productivity of female caribou ( Rangifer tarandus (L., 1758)) in two large migratory herds in the Quebec–Labrador peninsula (Canada), the George and the Feuilles herds. Females from the George herd were in better summer condition than those from the more abundant Feuilles herd in 2001–2002, while it was the opposite in 1988 when the Feuilles herd was less abundant than the George herd. Summer nutrition followed the same pattern between herds through time. Spring body condition of females in the George herd declined from 1976 to the mid-1980s during early population growth. Fall condition, however, did not change from 1983 to 2002 when caribou numbers first peaked and later declined. Pregnancy rates were inversely related to herd size in both herds. Vegetation quality (NDVI) in June was significantly related to body proteins in the fall. Albeit unusual for a northern ungulate, body fat increased from fall to spring in the George herd. We conclude that a relatively small and highly grazed summer range, as well as density-dependent effects, affected summer nutrition and the need to continue lipogenesis during winter.
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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 | 0.000 | 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".