Mapping the distribution of the Sunda pangolin (Manis javanica) within natural forest in Sabah, Malaysian Borneo
Bibliographic record
Abstract
Pangolins are the most trafficked mammals in the world and are severely threatened by poaching the loss, degradation, and fragmentation of habitat. In Malaysian Borneo, conservation initiatives for the Sunda pangolin ( Manis javanica ) are hindered by a paucity of data on their distribution and population size. Using MaxEnt niche modelling and consolidated species location data, we projected the distribution of Sunda pangolins in Sabah. Additionally, we assessed the accessibility of their forest habitats to humans to understand potential threats. Our model indicated that, as of 2015, approximately half of Sabah’s land area (39,530 km²) is suitable for pangolins, with 43% in protected forests, 38% in production forests, and 19% outside of these areas. Alarmingly, our data suggest that nearly all (91%) of these suitable habitats are relatively easily accessible to poachers. Our findings provide a state-level baseline understanding of Sunda pangolin distribution and assess potential threats in Sabah. These can inform short- and long-term conservation management plans for pangolin to safeguard this critically endangered 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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".