Impact of Lighting Condition and Social Isolation on Rats' Playfighting Behaviour
Bibliographic record
Abstract
Playfighting in rats is a well-documented phenomenon, however, studies frequently differ in terms of the conditions under which play behaviour is assessed. This study examined the impact of lighting condition and social isolation on play, two conditions which vary in literature. The goal was to quantify and advance the understanding of optimal conditions for promoting playfighting behaviour in rats. Twenty-four male Long-Evans rats were randomly assigned a lighting condition (complete darkness vs. low mixed red-white light) and social isolation condition (0 hours vs. 5 hours vs. 24 hours). Rats were habituated in cagemate pairs to a plexiglass test chamber (60 x 60 x 40 cm) under their respective lighting conditions for three days prior to testing. Prior to the test day, cagemate pairs were randomly selected to be isolated from their play partners for different durations. After their respective isolation periods, cage-mate pairs of adolescent rats (PD30-37) were video-taped freely interacting in the test chamber for 10-minutes and their play behaviour was scored in NOLDUS by a trained coder. Data were analyzed in SPSS using a 2x3 ANOVA. Rats tested in complete darkness displayed higher rates of nape attacks (p = 0.008) and pinning (p = 0.002), two measures used to quantify playfighting. Post-hoc testing revealed that rats isolated for 24-hours prior to testing displayed higher rates of nape attacks (p = 0.028) and pins (p = 0.005) compared to non-isolated rats, but there were no other differences between other isolation conditions. These findings suggest that the conditions under which rats are tested can impact their play behaviour, driving differences in rates of commonly scored play behaviours. The data suggest it is ideal to assess rats’ play behaviour in complete darkness after at least 24-hours of social isolation to optimize baseline levels of playfighting.
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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 | 0.001 |
| 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".