An Ethogram Developed on Captive Eastern Coyotes <em>Canis latrans</em>
Bibliographic record
Abstract
We studied capture Eastern Coyotes (Canis latrans) from 27-585 days of age and compiled an ethogram on them. A total of 72247 15-sec samples were taken, amounting to 301 h of field time varying between 59.4–61.3 h per Coyote. A total of 540 behavioral patterns was observed amongst the 16 behaviour categories ranging from 9 (miscellaneous) to 72 (explore/investigate) action patterns per parent category. The 16 parent categories that we believed best described and appropriately sorted the behavioural actions were resting, sitting, sitting1, sitting2, standing, traveling, explore/investigating, hunting, feeding, infantile, greeting, self play, play initiating, playing, agonistic, and miscellaneous. Exploring accounted for >31% of all of the behaviours observed with resting and sitting (combined), standing, traveling, and play as categories decreasing in order of most to least frequent. Despite some omissions in our ethogram and drift associated with its ongoing development, we believe that the large amount of data collected made it rigorous enough to be a useful guide for the species. We argue that although future research will no doubt add to and/or modify components of it, its ease of use in the field (in captivity or in the wild) and it being the first complete ethogram described for the species, make it a useful tool for future researchers.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".