Wariness of coyotes to camera traps relative to social status and territory boundaries
Bibliographic record
Abstract
The primary objective of this study was to develop a better understanding of coyote (Canis latrans) wariness particularly as it related to social status. We determined that territory status (controlling alpha, resident beta, or nonterritorial transient) affected vulnerability to photo-capture by infrared-triggered camera systems. All coyotes were wary of cameras, leading to relatively low numbers of photo-captures, most of which occurred at night. Alphas were significantly underrepresented in photographs and were never photo-captured inside their own territories. Betas were photographed inside and outside their territories, whereas transients were most often photographed on edges of territories. Both alphas and betas were photographed more often on territorial edges when outside their territories. We next addressed the question of how alphas were better able to avoid photo-capture. Alphas tracked human activity within their territories and presumably learned the locations of cameras as they were being set up. They did this either by approaching our location directly or by moving to a vantage point from where they could observe us. Betas and transients either withdrew or did not respond to human activity. Trials in which a dog was present were more likely to elicit an approach response from alphas. Avoidance of camera stations and the tracking of human activity implied wariness toward objects or locations resulting from their learned association with human presence rather than neophobia toward the objects themselves.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".