Quantifying the road‐effect zone for a critically endangered primate
Bibliographic record
Abstract
Abstract The global road network is expanding at an unprecedented rate, threatening the persistence of many species. Yet, even for the most endangered wildlife, crucial information on the distance up to which roads impact species abundance is lacking. Here we use ecological threshold analysis to quantify the road‐effect zone (REZ) for the critically endangered western chimpanzee ( Pan troglodytes verus ). We found: (1) the REZ extends 5.4 km (95% CI [4.9–5.8 km]) from minor roads and 17.2 km (95% CI [15.8–18.6]) from major roads, the latter being more than three times wider than a previous estimate of the average REZ for mammals; and (2) only 4.3% of the chimpanzees’ range is not impacted by existing roads. These findings reveal the high sensitivity and susceptibility of nonhuman primates to roads across West Africa, a region undergoing rapid development, and can inform the implementation of more effective guidelines to mitigate road impacts.
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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) | 0.001 | 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 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".