Annual Variation in Habitat Use by White-footed Mice, <em>Peromyscus leucopus</em>: The Effects of Forest Patch Size, Edge and Surrounding Vegetation Type
Bibliographic record
Abstract
White-footed Mice (Peromyscus leucopus) were trapped for two years in the exterior matrix, edge, and interior forest habitat sections of six forests patches in a fragmented agricultural landscape. We used data on the capture locations of P. leucopus individuals from the two years, which differed in rainfall (i.e., summer of 2000 with 50% more rain than summer of 1999), to assess how patch size, edge habitat, and surrounding habitat type influence habitat use and movements in populations of this forest habitat generalist. We found that the proportion of individuals subsequently captured in the forest edge from the exterior was 16 times greater in the wet year than in the dry year and approximately twice as many P. leucopus were not subsequently recaptured from the exterior matrix in the dry year compared to the wet year. For each year, captures between habitats did not differ in relation to patch size, edge forest habitat, or exterior matrix type. These results illustrate the generalist habitat preferences of P. leucopus, but emphasize annual variation in their behavior and distribution.
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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".