Regional heterothermy in <i>Megasoma gyas</i> is not related to active heat dissipation by the horns
Bibliographic record
Abstract
Abstract Animals rely on physiological and behavioral processes to maintain thermal balance. Some animals, however, bear structures that help dissipate excess heat when body temperatures rise. Although widespread in animals, animal weapons—exaggerated morphological structures with multiple characteristics that can make them good at dissipating heat—have rarely been studied in the context of thermoregulation. Here, we investigated whether the horns of the Rhinoceros Beetle ( Megasoma gyas ) acted as a thermal window. We heated live and dead beetles to 30ºC and allowed them to cool to 20ºC while measuring surface temperature changes in four body regions: the cephalic and thoracic horns, the scutellum, and the abdomen. If horns actively dissipated heat, they would show the lowest cooling rate among body regions. Contrary to this expectation, we found that the cephalic horn had the highest cooling rate, followed by the abdomen, thoracic horn, and scutellum, respectively. This suggests that the horns are not used for active heat dissipation in M. gyas . The low cooling rate of the scutellum can be explained by the presence of large flight muscles in the thorax, which play a role in heat generation, but could also aid in heat dissipation by pumping hemolymph across tagmata or through the low-insulated cuticle to prevent thoracic overheating. We also demonstrate that beetles show regional heterothermy even in the absence of exercise or stress. As such, we propose that regional heterothermy may result from both active (control of hemolymph flow) and passive (heat dissipation through poorly insulated structures) processes within individuals.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".