Thermoregulation of transgenic growth hormone mice
Bibliographic record
Abstract
Transgenic growth hormone (TG) mice (Mus musculus L., 1758) obtain enhanced growth via compensatory feeding at intermediate sizes and via higher growth efficiency. The latter involves diverting resources from other functions such as locomotion and wakefulness. Thermogenesis is a major expense for small mammals, so we explored whether TG mice express a trade-off between growth and thermoregulation. TG mice are hypothermic and cannot maintain their body temperature under cold stress. TG mice showed initial enlargement of brown adipose tissue and subsequent age-related decreases not seen in controls. Some TG mice became torpid after fasting durations not known to affect other mice. On a high-calorie diet, TG mice had higher body temperatures even though controls did not. Our background strain developed obesity on a high-protein and high-fat diet, and on a diet supplemented with carbohydrates, whereas TG mice never developed obesity. White adipose tissue deposits of TG females were relatively larger, but those of TG males were relatively smaller, than those of controls fed standard food. We also found significant effects of the three experimental diets, as well as gender, age, body mass, ambient temperature, and behavioural activity, on rectal temperatures of TG mice and controls in a large breeding colony. Thermogenesis of TG mice fed standard food appears energetically constrained, likely contributing to enhanced growth efficiency.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".