Heat dissipation limit theory and the evolution of avian functional traits in a warming world
Bibliographic record
Abstract
Summary It is generally assumed that animal energy expenditure is limited by energy acquisition. In a series of publications, Speakman, Król and colleagues argue that the capacity to dissipate metabolic heat may also limit maximum rates of energy expenditure in endotherms (heat dissipation limit theory – HDL theory). The implications of the HDL theory for the evolution of avian functional traits are substantial and open fascinating research perspectives. Notably, the HDL theory leads us to (i) link elevated bird body temperatures with their capacity to achieve higher rates of heat loss and of energy expenditure, (ii) reconsider the evolution of avian plumage patterns and speculate upon the capacity of white birds to achieve higher field metabolic rates than darker relatives, (iii) hypothesize that the avian brood patch also functions as a thermal window allowing birds to shed excess heat and (iv) revise our current view of the adaptive significance of limited plumage thermal insulation in great cormorants. Such features have important implications for the capacity of birds to cope with global warming and for the design of mechanistic models of animal energetics aiming at predicting their responses to changing environmental conditions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".