Food habits and space use of gray foxes in relation to sympatric coyotes and bobcats
Bibliographic record
Abstract
To investigate interspecific relationships between gray foxes (Urocyon cinereoargenteus) and sympatric coyotes (Canis latrans) and bobcats (Lynx rufus), we quantified occurrence of food items in carnivore scats and used relative abundances of scats on transects to assess space use. Dietary-overlap indices between the two canid species were high during summer and fall ([Formula: see text] = 0.89) when fruits were prevalent in scats of both species, and were lower during winter and spring ([Formula: see text] = 0.70) when fruits were less available. Foxes differed most from coyotes in their relatively less frequent ungulate consumption. Foxbobcat dietary-overlap indices were relatively low in summer and fall ([Formula: see text] = 0.37) and greater in winter and spring ([Formula: see text] = 0.74). Foxes differed most from bobcats in their more frequent consumption of fruits and less frequent consumption of lagomorphs. Abundance of fox scats was positively correlated with abundance of coyote scats during both winterspring (r = 0.52, p = 0.02) and summerfall (r = 0.75, p < 0.001) and with abundance of bobcat scats during winterspring (r = 0.59, p < 0.01) and summerfall (r = 0.22, p > 0.10). Thus, despite similarities in diet, we found no evidence that gray foxes avoided these larger predators in space.
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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 | 0.000 |
| 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".