A break from the pups: The effects of loft access on the welfare of lactating laboratory rats
Bibliographic record
Abstract
Rats (Rattus norvegicus) bred for research are typically confined with their litters until weaning, but will spend time away from pups when given the opportunity. We aimed to assess how dam welfare is affected by the ability to escape from their pups. Rat dams (n = 16) were housed in cages either with or without an elevated loft. We measured time dams spent in lofts, time spent nursing, and affective states using elevated plus maze and anticipatory behavior testing. We predicted that 1) dams housed with lofts would use them increasingly as pups aged, 2) dams without a loft would spend more time passively nursing (i.e. initiated by pups rather than the dam) and more total time nursing as pups aged, and 3) dams housed with lofts would show evidence of a more positive affective state. Dams housed with lofts spent more time in the loft with increasing pup age; dams spent on average (mean ± SE) 27 ± 5% of their time in the loft when pups were 1 wk old, increasing to 52 ± 5% of their time at 3 wks. When pups were 3 wks old, dams with lofts spent less time passively nursing (10 ± 2% of total time, compared to 27 ± 4% for dams without a loft) and less time nursing overall (36 ± 4% of time versus 59 ± 2% for dams without a loft). Rats without loft access showed increased anticipatory behavior potentially indicative of negative affective state (24.5±1.8 behaviors per minute in wk 3 compared to 18.8±1.0 in wk 1). These findings indicate that rat dams in laboratories choose to spend time away from their pups when provided the opportunity, particularly later in lactation; an inability to do so is associated with increased passive nursing and negative affect.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".