Mammalian Diet and Broad Hunting Strategy of the Dingo (Canis familiaris dingo) in the Wet Tropical Rain Forests of Northeastern Australia<sup>1</sup>
Bibliographic record
Abstract
ABSTRACT The diet of dingoes (Canis familiaris dingo) in the Australian Wet Tropics was examined by analyzing 383 dingo scats collected throughout the region for the presence of mammal prey remains. The scats yielded 29 native and 4 introduced mammal prey species from 14 families. The most important species in terms of percentage occurrence in the scats were Melomys cervinipes (22.2%), hoodon macrourus (17.0%), Perameles nasuta (12.5%), and Thylogale stigmatica (12.5%). The most important families were Muridae (37.1%), Peramelidae (29.5%), and Macropodidae (25.8%). Examination of small‐scale habitat preferences revealed species that preferentially use the forest edge ranked significantly higher in the diet than those that do not, and species that are terrestrial ranked higher in the diet than those that are arboreal. Relative abundance was also a significant factor in the ranked dietary occurrence of each species, with abundant species ranked significantly higher than those that are less abundant. These results suggest that dingoes in the Australian Wet Tropics are opportunistic predators of a wide variety of mammal species, with abundant terrestrial and forest edge‐dwelling taxa the most susceptible to predation.
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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 | 0.000 |
| 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) | 0.001 | 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".