A strategic approach to mitigating the impacts of wild canids: proposed activities of the Invasive Animals Cooperative Research Centre
Bibliographic record
Abstract
Wild canids (wild dogs and European red foxes) cause substantial losses to Australian livestock industries and environmental values. Both species are actively managed as pests to livestock production. Contemporaneously, the dingo proportion of the wild dog population, being considered native, is protected in areas designated for wildlife conservation. Wild dogs particularly affect sheep and goat production because of the behavioural responses of domestic sheep and goats to attack, and the flexible hunting tactics of wild dogs. Predation of calves, although less common, is now more economically important because of recent changes in commodity prices. Although sometimes affecting lambing and kidding rates, foxes cause fewer problems to livestock producers but have substantial impacts on environmental values, affecting the survival of small to medium-sized native fauna and affecting plant biodiversity by spreading weeds. Canid management in Australia relies heavily on the use of compound 1080-poisoned baits that can be applied aerially or by ground. Exclusion fencing, trapping, shooting, livestock-guarding animals and predator calling with shooting are also used. The new Invasive Animals Cooperative Research Centre has 40 partners representing private and public land managers, universities, and training, research and development organisations. One of the major objectives of the new IACRC is to apply a strategic approach in order to reduce the impacts of wild canids on agricultural and environmental values in Australia by 10%. In this paper, the impacts, ecology and management of wild canids in Australia are briefly reviewed and the first cooperative projects that will address IACRC objectives for improving wild dog management are outlined.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".