Affectivity during social behaviour in a schizophrenic-like rat
Bibliographic record
Abstract
Introduction Rats are social animals that produce high-frequency whistles said to reflect their underlying affective state. Injecting rats with a glutamate agonist (domoic acid) at a sensitive period of brain development, models aspects of schizophrenia. This is known as the neonatal DOM model. Aims We investigated whether DOM rats display altered social behaviour – as seen in patients with schizophrenia – using their high-frequency whistles as a proxy for the emotional valence of social situations. Methods We used 19 male Sprague Dawley rats, injected with either a low-dose of domoic acid or saline at postnatal days 8 to 14. The social behaviour of the rats was investigated at four levels: – anticipation of social interaction; – dyadic encounter; – three-chamber test; – tickling. Tests were carried out at postnatal days 34 to 40 and 50 to 56. Rat whistles were recorded on all days of testing. Results In progress. Conclusions The interest in rat whistles as a supplement to traditional behavioural tests has increased. New software allows for detailed qualitative analysis of the whistle subtypes and thus new complexity to their interpretation. This study can help unravel information encoded in the whistles and shed light on the social behaviour of the DOM rat thus investigating it is applicability as a model of schizophrenia. Disclosure of interest The authors have not supplied their declaration of competing interest.
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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) | 0.001 | 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) | 0.003 | 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".