Preference for bedding material in Syrian hamsters
Bibliographic record
Abstract
This study aimed to determine whether Syrian (golden) hamsters, Mesocricetus auratus, prefer certain bedding materials and whether bedding material can affect paw condition, body weight gain and wheel-running activity. In a first experiment, 26 male hamsters had access to two connected cages, each cage containing a different bedding material (either pine shavings, aspen shavings, corn cob or wood pellets). In a second experiment, 14 male hamsters had access to four connected cages that contained the different bedding materials and also a piece of paper towel to serve as nest material. In a third experiment, 30 male hamsters were each placed in a single cage, 10 of them with pine shavings, 10 with aspen shavings and 10 with corn cob, and they were monitored for 50 days. Significant preferences in the first experiment were: pine shavings over aspen shavings, corn cob over wood pellets, pine shavings over corn cob and aspen shavings over wood pellets (aspen shavings versus corn cob was not tested). However, there was no significant preference expressed in the second experiment, suggesting that the general preference for shavings in the first experiment was based on bedding material suitability as a nesting material. No significant effect of bedding material on paw condition, body weight gain and wheel-running activity was detected. None of the four bedding materials tested in this study can be judged to be inappropriate in the short term if nesting material is added to the cage and if the litter is changed regularly.
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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) | 0.002 | 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".