Decreased thermoregulatory precision contributes to the hypoxic decrease in body temperature in lizards
Bibliographic record
Abstract
Low oxygen induces a decrease in body temperature (T b ) in most vertebrates. This response has been attributed to a decrease in the in the T b set‐point, protecting organs from oxygen depletion. In addition, hypoxia decreases activity levels and, therefore, the propensity to move. In ectotherms, where thermoregulation is mainly behavioural, hypoxia is, thus, expected to impact the precision of thermoregulatory control. To determine if thermoregulatory precision is indeed decreased in hypoxia, we evaluated the variability and level of thermoregulation of bearded dragons at five oxygen levels in three different experimental settings: a dynamic temperature‐choice shuttle box, a constant temperature dual‐choice shuttle box, and a thermal gradient. A significant increase in the size of the T b range was observed at the lowest oxygen level (4% O 2 ) in the dynamic shuttle box, but not in the thermal gradient. This was accompanied by a T b drop of 2‐ 4°C, the drop being greatest when T b must be actively defended. Situations that force lizards to continually choose temperatures lead to an increase in T b variability, which is further exaggerated in hypoxia. This study reveals that a decrease in thermoregulatory precision caused by a diminished propensity to move or effect appropriate thermoregulatory responses may partially explain the lowering of T b observed in hypoxic ectotherms.
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 | 0.000 | 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".