Data for non-target interactions and humaneness evaluation on a captive-bolt trap for commensal rodents
Bibliographic record
Abstract
The Goodnature® A24 automatic rat trap is a self-resetting captive-bolt trap powered by pressurized CO2. Little research has examined the humaneness of the trap or its potential to harm non-target mammals and birds. This study aimed to identify potential risks to non-target animals. 17 traps, each paired with a motion-activated video camera, were deployed at two sites where rodents were present. In a nine-week study, traps were baited but not activated, and a blocking device (“blocker”) was used in a cross-over design to evaluate its potential at reducing non-target strikes. Once the researchers were confident in avoiding non-target strikes, the traps were activated and recorded for 19 weeks across two different locations to evaluate humaneness. Surprisingly, only 11 trap triggers and eight kills were observed across the two locations. The eight observed kills included 3 house mice, 4 deer mice, and 1 grey squirrel. The Goodnature® A24 traps presented low risks to non-target animals, and the use of blockers effectively removed the risks to the common non-target species with the exception of one shrew in Study 1 and one squirrel in Study 2.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.015 |
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".