Patterns of winter locomotion and foraging in two sympatric marten species:<i>Martes martes</i>and<i>Martes foina</i>
Bibliographic record
Abstract
Modes of area searching and exploratory behaviour of the sympatric pine marten, Martes martes (L., 1758), and stone marten, Martes foina (Erxleben, 1777), were studied by snow-tracking in two regions of Poland. The accuracy of identifications of the two species on the basis of their snow tracks was assessed by DNA analysis of their faeces, as collected on the tracks; identifications were found to be correct in 88% of cases. Although most activities of the two species were concentrated on the forest floor, pine martens climbed trees, moved in tree crowns, and searched the bases of tree trunks and tree hollows more frequently than stone martens. In contrast, stone martens were more inclined to search for food in brushwood and piles of wood, and visited logged areas and garbage dumps more frequently. Pine martens avoided man-made objects and barriers such as roads and passed through open areas with reluctance. Such behavioural traits make this species particularly vulnerable to forest fragmentation and human activity in forests. Stone martens often explored woodless areas and inhabited buildings, which allowed them to use habitats substantially transformed and intensively explored by humans. The future coexistence and relative numbers of the two martens in forest habitats will depend on the mode of forest management and on the existence of effective migratory corridors connecting forest 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 | 0.001 | 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) | 0.000 | 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".