Wolf, <em>Canis lupus</em>, Visits to White-tailed Deer, <em>Odocoileus virginianus</em>, Summer Ranges: Optimal Foraging?
Bibliographic record
Abstract
We tested whether Wolf (Canis lupus) visits to individual female White-tailed Deer (Odocoileus virginianus) summer ranges during 2003 and 2004 in northeastern Minnesota were in accord with optimal-foraging theory. Using GPS collars with 10- to 30-minute location attempts on four Wolves and five female deer, plus eleven VHF-collared female deer in the Wolves' territory, provided new insights into the frequency of Wolf visits to summer ranges of female deer. Wolves made a mean 0.055 visits/day to summer ranges of deer three years and older, significantly more than their 0.032 mean visits/day to ranges of two-year-old deer, which generally produce fewer fawns, and most Wolf visits to ranges of older deer were much longer than those to ranges of younger deer. Because fawns comprise the major part of the Wolf's summer diet, this Wolf behavior accords with optimal-foraging theory.
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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 | 0.000 | 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".