The propensity of spotted-tailed quolls (Dasyurus maculatus) to encounter and consume non-toxic meat baits in a simulated canid-control program
Bibliographic record
Abstract
Using a biomarker, we assessed the propensity of spotted-tailed quolls (Dasyurus maculatus) to encounter and consume non-toxic meat baits, ordinarily laced with the poison 1080 (sodium monofluoroacetate) and deployed for control of wild dogs (Canis lupus dingo, Canis familiaris and hybrids of the two) in southern Australia. In the first experiment, 60 unpoisoned meat baits injected with Rhodamine B were placed on the surface of the ground at 250-m intervals along two separate transects crossing an open woodland study area. One week after placement, a range of animals, including quolls, had removed all baits. Microscopic assay of whisker samples collected from live-captured quolls later revealed that 6 of 10 (60%) animals were positive for the biomarker, indicating that they had encountered and consumed baits. In the second experiment, conducted at the same site one year later, 150 similarly prepared meat baits were delivered aerially from a helicopter along the same transects, at a rate of one bait every 100 m. Eight of 17 quolls (47%) were found to have encountered and consumed at least one and up to five baits. Combined with previous studies, our results reaffirm that surface or aerial baiting operations for wild dogs may place local quoll populations at risk. However, further research is necessary to establish the relationship between this risk and actual mortality levels during such baiting operations since there are a number of factors that may influence the toxicity of baits for spotted-tailed quolls in a field situation as well as the danger those baits may pose.
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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 | 0.001 |
| 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".