Factors affecting space use by wild boars (<i>Sus scrofa</i>) in high-elevation tropical forests
Bibliographic record
Abstract
The wild boar (Sus scrofa Linnaeus, 1758) is considered one of the 100 worst invasive species in the world and is present in the high-elevation forests in Brazil. Our objective was to understand how landscape and atmospheric conditions affect space use by wild boars. We hypothesized that wild boars would be more frequent at lower elevations, warmer and wetter forested areas, and away from human disturbances. After three years of data collection (2013–2016) using 16 camera traps, 881 independent records were obtained with a mean of 4.44 ± 9.25 pigs per record. Wild boar frequency of occurrence was higher at lower elevations, in more humid and warmer areas, and farther away human disturbance factors, corroborating our initial hypothesis. Understanding space-use patterns of wild boars is necessary for the design of management strategies that target areas of more intense usage, as well as for defining more effective population-control techniques.
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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 | 0.001 |
| 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) | 0.001 | 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".