The thermogenesis of digestion in rattlesnakes
Bibliographic record
Abstract
Some snakes have a feeding regime characterized by the infrequent ingestion of relatively large meals, causing impressive increments in post-prandial metabolism. Metabolism remains elevated for many days, while digestion proceeds, resulting in considerable investment of time and energy. Snakes actively adjust thermoregulatory behavior to raise their body temperature during digestion, exhibiting a post-prandial thermophilic response that accelerates digestion at the expense of higher metabolic rates. In the present study, we investigated the possibility that endogenously derived heat, originating as a byproduct of the post-prandial increase in metabolism, could itself contribute to the elevated body temperature during digestion in the South American rattlesnake Crotalus durissus. We assessed heat production, at a constant environmental temperature, by taking infrared (IR) images of snakes during fasting and after being fed meals varying from 10% to 50% of their own body masses. Our results show clearly that digesting rattlesnakes have significantly increased body temperatures, even when precluded from adjusting their thermoregulatory behavior. The feeding-derived thermogenesis caused the surface body temperature of rattlesnakes to increase by 0.9-1.2 degrees C, a temperature change that will significantly affect digestive performance. The alterations in body temperature following feeding correlated closely with the temporal profile of changes in post-prandial metabolism. Moreover, the magnitude of the thermogenesis was greater for snakes fed large meals, as was the corresponding metabolic response. Since IR imaging only assesses surface temperatures, the magnitude of the thermogenesis and the changes in deep core temperature could be even more pronounced than is reported here.
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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".