Long-term effects of cage-cleaning frequency and bedding type on laboratory rat health, welfare, and handleability: a cross-laboratory study
Bibliographic record
Abstract
Cage-cleaning is necessary for a hygienic environment, but since rats communicate using scent, they might suffer if their cages are cleaned too frequently. Male rats (Sprague-Dawley and Wistar) were kept for five months across four animal units. Their cages were cleaned twice-weekly, weekly, or every two weeks, and contained either aspen woodchips or absorbent paper bedding. Aggression, injuries and general health, weight gain, chromodacryorrhoea (a stress-related Harderian gland secretion), handleability, and lung pathology were monitored, as was in-cage ammonia. Cleaning frequency had no clear impact on rat welfare, although frequent cleaning decreased ammonia concentrations and handleability, and non-aggressive skirmishing was highest in weekly cleaned rats. Surprisingly, bedding type did not affect ammonia, but all ammonia readings were unexpectedly low. However, rats kept on aspen had greater sneezing rates and lung pathology than those on paper bedding, but also had higher body weights. The results raise concerns about aspen bedding, which is relatively inert compared with other wood beddings, but nevertheless more harmful than paper. Animal unit significantly affected eight of the 11 variables tested, having interactive effects on five of them. The study also demonstrates the interactive effects of different animal units, casting doubt on the feasibility of standardization. We explored multiple variables of interest, so all findings require confirmation through further work. Nevertheless, cage-cleaning rates seem to affect socially housed male rats little, while bedding type has important effects on rat health.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.002 |
| 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".