Stress-induced hyperthermia in the rat: comparison of classical and novel recording methods
Bibliographic record
Abstract
Stress causes a rise in body temperature in laboratory animals (stress-induced hyperthermia). However, the direct effect of common stressors in animal research, i.e. transportation between holding and test rooms or isolation of animals, on body temperature has not been investigated to its full extent. To address this question, it is important to have a reliable and simple monitoring technique, which does not induce stress itself. In the present study, we investigated stress-related changes in body temperature of F344/Hw rats after (1) moving the cage within the holding room, (2) moving the cage from the holding room to another test room and (3) social deprivation (isolation). A combination of two different body temperature recording methods was used to clarify their accuracy and stress-inductive character: rectal temperature recording and peritoneal implanted temperature sensors (Thermochron iButtons).The results demonstrate that (1) different stressors induce a significant rise in body temperature, (2) which is detectable for more than 60 min and (3) it is of importance to standardize temperature recording methods in order to avoid confounding effects of the recording method itself. Furthermore, Thermochron iButtons are more accurate and reliable for body temperature studies than rectal recordings.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".