Seasonal space use of transient and resident coyotes (<i>Canis latrans</i>) in North Carolina, USA
Bibliographic record
Abstract
Coyote (Canis latrans Say, 1823) is a recent immigrant into eastern United States and little is known about the species’ space use and movement in the region. We compared space use and movement of radio-collared coyotes among biological seasons. We captured and collared 30 coyotes from February through May 2011 and collected 85 386 GPS locations through October 2012 at Fort Bragg Military Installation. We defined four biological seasons according to coyote life history: breeding (December–February), gestation (March–May), pup-rearing (June–August), and dispersal (September–November). Out of 27 radio-collared individuals, we identified 10 as transient and 11 as resident based on home-range size and variability across seasons; 6 switched their status and were classified as intermediate. We observed low variability of core-area size across seasons for resident males and females, whereas we documented high variability for transient males. Movement rate of resident coyotes during spring (449.75 m/h) was greater than summer (295.33 m/h), whereas movement rates did not differ between any other seasons. For transient coyotes, movement rate during summer (283 m/h) was less than fall (374.73 m/h), spring (479.85 m/h), and winter (488.5 m/h). Some coyotes adjusted their residency status seasonally and other individuals dispersed large distances (>200 km).
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".