What's hot and what's not: defining torpor in free-ranging birds and mammals
Bibliographic record
Abstract
With the development of small implantable data loggers and externally attached temperature-sensitive radio transmitters, increasing attention is being paid to determining the thermoregulatory strategies of free-ranging birds and mammals. One of the constraints of such studies is that without a direct measure of metabolic rate, it is difficult to determine the significance of lowered body temperatures. We surveyed the literature and found that many different definitions have been used to discriminate torpor from normothermy. Many studies use arbitrary temperature thresholds without regard for the normothermic body temperature of the individuals or species involved. This variation makes comparison among studies difficult and means that ecologically and energetically significant small reductions in body temperature may be overlooked. We suggest that normothermic body temperature for each individual animal should be determined and that torpor be defined as occurring when the body temperature drops below that level. When individuals' active temperatures are not available, a species-specific value should be used. Of greater value, however, are the depth and duration of torpor bouts. We suggest several advantages of this definition over those used in the past.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".