Broadcasting American red squirrel vocalizations influences detection probability
Bibliographic record
Abstract
Territorial responses by North American red squirrels (Tamiasciurus hudsonicus) to conspecifics vary seasonally with peaks during mating and dispersal periods. Broadcast of squirrel vocalizations during surveys may elicit territorial defense behaviors such as calling and movement that make individuals more available for detection, with implications for subsequent occupancy and abundance analyses. We examined the effect of vocalization broadcasts on detection probability during point counts throughout a 14-month period at two locations (year-round study) and during two summers at a third location (summer-only study) on Newfoundland, Canada. Overall detection probability based on sight and sound varied seasonally but the use of vocalization broadcast consistently enhanced detection probability. Squirrels were also more likely to be seen during vocalization broadcast survey periods than during silent point counts. Response to vocalization broadcast was highest when local population density was lowest. Higher detection probability during the initial silent periods of our surveys, when population density was high, likely reflects the greater chance of spontaneous vocalizations in response to the behavior of neighbors.
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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 | 0.002 |
| 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".