Proposed research on home ranges and resource use of the water monitor lizard, <i>Varanus salvator</i>
Bibliographic record
Abstract
Throughout the world, population growth and conversion of land for human development increase the potential for areas of human and wildlife activity to overlap. Anthropogenic effects on animal behavior may have ecological consequences if response to human disturbance or dependence on anthropogenic food sources prevents wildlife from carrying out traditional ecological roles. The presence of large predatory species such as the water monitor lizard, Varanus salvator, in areas of human development may also result in conflict if animals become habituated to the presence of humans or begin to compete for resources. Understanding anthropogenic effects on V. salvator resource use and activity is a key to predicting behavior and informing conflict mitigation in systems where humans and V. salvator coexist. V. salvator home ranges and resource use will be investigated on Tinjil Island, Indonesia, where radiotelemetry will be used to track V. salvator individuals across areas of varying human presence in both wet and dry seasons. Greater insight into anthropogenic influences on V. salvator resource use will contribute increased knowledge of V. salvator's ecological role in undisturbed and human-altered communities and can serve to inform the prevention of human–V. salvator conflict.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".