The scavenging behaviour of the Australian Raven (Corvus coronoides): patterns and influencing factors
Bibliographic record
Abstract
The Australian Raven (Corvus coronoides) is a widespread, abundant corvid which is often considered a pest species, due to the thought that it predates on livestock, ruin crops, and is often seen feeding on refuse, in both urban and rural areas. The species is known to feed on a range of material from seeds in ploughed fields to human refuse and decomposing organic material. A large proportion of its diet consists of carrion, and as such, the Australian Raven is an effective detrivorous species capable of removing and consuming dead and decomposing carcasses. This research examined the scavenging pattern of the Australian Raven on domestic pig (Sus scrofa) carcasses at four different locations surrounding Perth, Western Australia. Domestic pig carcasses were sacrificed and placed in outdoor environments and the carcasses were filmed using infrared cameras with time-lapse image capture. The number of feeding events, length of feeding, material being fed upon, and associated weather data were recorded. Furthermore, the influences of location, season and life cycle of the Australian Raven on scavenging behaviour is examined. It was found that raven scavenging intensity was greatest during spring and as an omnivore there was significantly higher feeding on both flesh and insects in one event than either material on its own.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".