Basking in the Australian water dragon Physignathus lesueurii; why do alpha males not respond to operative temperatures in the same way as adults and sub-adults?
Bibliographic record
Abstract
Abstract Observations have been made on the behaviour of the Australian water dragon Physignathus lesueurii in southeast Australia. Physical models that explore the thermal environment at a similar spatial level as real lizards were related to ontogenetic changes in lizard behaviour. Current theory predicts that a heliotherm will bask in open locations to optimise heating rates in order to attain target body temperatures as quickly as possible. Movement to shaded or partially shaded areas then maintains thermal stability. Regression equations of basking intensity in relation to operative temperatures were employed to test this theory. The behaviour of adults, which were not alpha males, and sub adults was in agreement with the prediction, but the behaviour of alpha males was not: the regression coefficient did not differ significantly from 0. In general, sub adult lizards were more active and fed more often than larger lizards although this relationship changed with different times of the day. The results suggest differing costs for thermoregulation for different size classes, particularly in alpha males where territory defence has a key role.
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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 | 0.000 | 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 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".