Human impacts on two endemic cassowary species in Indonesian New Guinea
Bibliographic record
Abstract
Abstract Cassowaries are important seed dispersers in tropical rainforests of New Guinea, but little is known about their population ecology or their responses to human disturbance. We used camera traps to measure the occurrence, local abundance, and activity patterns of northern cassowaries Casuarius unappendiculatus in lowland forests near Nimbokrang, Papua, and dwarf cassowaries Casuarius bennetti in the Arfak Mountains, West Papua. Our goals were to assess human impacts on cassowaries at multiple spatial scales and to measure their activity patterns over an elevational divide. At fine spatial scales local abundance of cassowaries was strongly reduced in areas frequented by humans. At larger spatial scales the distance to the nearest village or drivable road did not affect local abundance but altered the stage structure of the individuals detected, with a higher proportion of juveniles relative to adults. Local abundance of cassowaries was unrelated to site usage by introduced pigs. Both populations studied were strongly diurnal and their activity patterns were not significantly different. Efforts to control hunting remain critical to sustaining cassowaries and the seed dispersal services they provide.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".