Factors determining "gaps" in the distribution of a small carnivore, the common genet (<i>Genetta genetta</i>), in central Spain
Bibliographic record
Abstract
We studied the pattern of distribution of the common genet (Genetta genetta) in areas in mountains and plains of central Spain, in the middle of the range of the species. We evaluated the role of temperature, rainfall, and habitat features in determining the ecological limits of genet distribution. Genets were very scarce on plateaux and the upper parts of the mountains, but were widely distributed in lower mountain areas. Genets were present in areas with abundant shrub cover, high mean of the mean minimum temperature and high mean of mean winter temperatures. Survey routes at the same altitude (<1000 m) in the mountains (genets abundant) and on the plateaux (genets very scarce) also differed in some of these variables, with low values on the plateaux for shrub cover, mean of the mean minimum temperatures, mean of the mean winter temperatures, and annual rainfall. Genets originated in Africa, therefore they are probably ill-adapted (morphologically and physiologically) for the cold conditions predominating in most of central Spain. Their preference for shrubby habitats may be linked to a greater availability of food and low risk of predation. Intermediate levels of rainfall may be correlated with higher temperatures, the key factor hypothesized to affect the distribution of this species. The distribution of the common genet fits a multimodal model, with peaks (presence) and valleys (absence) in the middle of its range, indicating that location in a particular part of the range is not a prior indicator of habitat suitability for the species.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".