A strategic approach to mitigating the impacts of wild canids: proposed activities of the Invasive Animals Cooperative Research Centre
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it