The impact of live trapping and trap model on the stress profiles of<scp>N</scp>orth<scp>A</scp>merican red squirrels
Bibliographic record
Abstract
Abstract Live‐capture is a necessary component for the scientific study and management of most mammals, but it may negatively affect their health and physiology. We compared blood parameters related to the stress response (nominal base levels) from red squirrels T amiasciurus hudsonicus after capture of up to 4.5 h in five different live trap models ( H ava‐hart, S herman, T omahawk 102, T omahawk 103 and ‘ S pecial S quirrel’ trap) with true base levels (obtained in less than three minutes). In addition, we evaluated the capture rate in the five trap models. We found that (1) prolonged time in live traps altered stress hormone concentrations compared with true base levels, but maximum corticosteroid‐binding capacity was unaffected; (2) squirrels captured in a trap model with reduced visibility (a roof cover – Hava‐hart) had significantly lower ( c. 50%) mean free cortisol levels compared with those captured in a trap model with full visibility ( T omahawk 102), but all other blood parameters were similar; (3) cortisol levels and white blood cell counts (mainly neutrophil counts) were positively related to duration of capture; (4) a non‐covered trap ( T omahawk 102) was most effective and fully covered trap ( S herman) was least effective at capturing squirrels. We discuss the use of effective, yet less stress‐inducing trap models to mitigate the stress caused by live‐capture on these animals. We conclude that covered traps such as the H ava‐hart may reduce trap‐induced stress in red squirrels, but at the same time also reduces their capture rates.
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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 | 0.001 | 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 | 0.001 |
| 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".