Movements and landscape use of camels in central Australia revealed by GPS satellite
Bibliographic record
Abstract
We analysed the movement of seven female camels collared in the Anangu Pitjantjatjara Yankunytjatjara Lands of South Australia. Understanding the movement patterns of feral camels and subsequently where high densities are likely to threaten biodiversity and cultural assets, provides land managers and government agencies with information and decision support tools to manage camel impacts. Accordingly, we tested if there were any seasonal changes in camel movement, any measurable separation between home range and migration, and any relationship between broader camel landscape use, rainfall and mountainous terrain. We fitted ARGOS GPS satellite collars to seven female camels in South Australia during August 2007 and found evidence to suggest that over a 12-month study period, some camels had returned to locations that they had previously visited. This cyclic movement pattern was more regular up to ~50 days, however, one collared individual returned to a previous location after 300 days. Despite only having a small sample size, we did find camels moving into areas that received higher rainfalls in the warmer months and possibly some attraction of these camels to steep mountainous terrain over this period.
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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 | 0.001 |
| 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".