Spatial structure and land-cover use in a low-density Mediterranean population of Eurasian badgers
Bibliographic record
Abstract
Eurasian badgers, Meles meles (L., 1758), have an extensive geographic range throughout which their social organization varies. Their capacity for intraspecific variation can now best be understood by studying them in landscapes that differ from the lush, lowland farmland where their tendency to form large groups has been most intensively investigated. Badgers in cork oak (Quercus suber L.) woodland are thus a priority for study, as this Mediterranean landscape provides an extreme contrast to those studied elsewhere. In this habitat in Portugal, we found 0.36–0.48 badgers/km 2 , one of the lowest population densities recorded in Western Europe. Here, individuals used seasonally stable home ranges that averaged 4.46 km 2 and that were occupied by 3–4 adults plus 3–4 cubs of the year. In this landscape, badgers selectively used cork oak woodland with understory and riparian vegetation. As predicted by the resource dispersion hypothesis, home-range size was positively correlated with food-patch dispersion. In southwestern Portugal, badgers depend upon an environmental mosaic such as olive groves and orchards and vegetable gardens for food and cork oak woodlands for shelter and protection.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".