Northern Bobwhite habitat selection during the nonbreeding season in a riparian corridor in Colorado
Bibliographic record
Abstract
Northern Bobwhites (Colinus virginianus) are a popular game species but also considered a species of conservation concern due to range-wide population declines. Colorado lies at the far northwest corner of the bobwhite range, where individuals generally face more extreme winter conditions than areas further south and east, where most bobwhite research has taken place. These edge-of-range climatic extremes may lead to differences in the utility and selection of various vegetation types and structures than those reported in studies from other regions in the bobwhite range. We used radio-marked bobwhites to assess habitat selection and movements during two nonbreeding seasons in a riparian corridor in northeastern Colorado. Bobwhites selected for greater visual obstruction (βvis = 0.026, SE = 0.005, P < 0.001), percent litter cover (βlitter = 0.017, SE = 0.006, P = 0.004), and percent bare ground (βbare = 0.013, SE = 0.007, P = 0.045). Mean daily movement distance was 247.3 m (SE = 10.4), and mean nonbreeding home range size was 50.3 ha (SE = 4.8). Surprisingly, we did not find selection for woody vegetation, which is commonly reported in other studies. Otherwise, our results were consistent with research from other regions, and confirm the importance of maintaining areas with high visual obstruction interspersed with bare patches.
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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 | 0.001 | 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".