Ecology of Stimson’s python (Antaresia stimsoni) in the MacDonnell Ranges of central Australia
Bibliographic record
Abstract
Stimson’s python (Antaresia stimsoni) is a small nocturnal python (Pythonidae) that occurs throughout Australia’s arid zone. Despite its wide distribution and localised abundance, no field-based studies have been undertaken on this species. We investigated activity patterns, habitat use, diet, and body sizes of A. stimsoni in the MacDonnell Ranges bioregion of the Northern Territory. Data were collected at night by road-cruising along a sealed road transect over 12 consecutive months. We found that the species copes with the extreme weather variability of arid Australia by remaining active over a broad range of air temperatures and maximising activity following rainfall when relative humidity is high and ground-dwelling frogs, a significant prey source, are likely to be abundant. A. stimsoni ceased activity only during the coldest months of the year. The species occurs in a range of vegetation types, with an apparent preference for riparian woodland, and its ability to thrive in the MacDonnell Ranges may be related to the abundance of rock-outcrops for refuge. Our results for diet and body size support previous research based on museum specimens, confirming that A. stimsoni feeds on a range of terrestrial vertebrates and is not sexually dimorphic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".