Habitat selection and use by a hybrid of white and Tibetan eared pheasants in eastern Tibet during the post-incubation period
Bibliographic record
Abstract
We investigated habitat selection and use by a recently discovered hybrid of the white eared pheasant (Crossoptilon crossoptilon) and Tibetan eared pheasant (Crossoptilon harmani) in the forests of eastern Tibet (93°39'E, 32°24'N) during the post-incubation period in 1995. The frequency of encountering molted feathers was used as an indicator of the relative abundance of eared pheasants in order to analyze patterns of habitat selection and use. Forests on south-facing slopes, dominated by the hollyleaf-like oak (Quercus aquifolioides) and Tibetan juniper (Sabina tibetica), were the habitats preferred by eared pheasants. North-facing slopes with coniferous forest, which is the most preferred habitat of eared pheasant species in other areas, were completely avoided, probably because moisture-heat conditions there are beyond the birds' physiological tolerance. We conclude that climatic conditions are the main determinant of macrohabitat selection by eared pheasant species. In preferred habitats, oak and juniper woodland accounted for a larger proportion of home ranges of family flocks. Daily movements of a flock might cover a large altitudinal range, from the base of the mountain to the area above tree line, with an apparent preference for sites that can be used for foraging and dusting.
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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 | 0.000 |
| 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".