Extinction bursts in rats trained to self-administer nicotine or food in 1-h daily sessions.
Bibliographic record
Abstract
Extinction bursts are characterized by a temporary increase in responding when drug access is withheld from rats trained to self-administer drugs of abuse. Thus far, one study has examined extinction bursts for nicotine self-administration using a 23-h access paradigm [1]. Here we examined extinction bursts using previously published and unpublished data in which rats were trained to self-administer nicotine (0.03mg/kg/infusion) or food pellets (as a comparator) in 1-h sessions under an FR5 schedule of reinforcement followed by 1-h extinction sessions. Analysis of response rates during nicotine self-administration (NSA) was indicative of a loading phase, as response rates were significantly higher at the beginning of the session, which was not observed for food self-administration. At the start of extinction for both food and nicotine, although sessional response rates did not increase, there was an increase in response rate during the first 5-min of the first extinction session relative to self-administration. This transient extinction burst following nicotine was observed in a minority of subjects and correlated with the number of nicotine infusions obtained during self-administration. This transient extinction burst following food was observed in all subjects. Nicotine and food produce more transient extinction bursts compared to other drugs of abuse and only for a minority of animals in the case of nicotine. This study supports the presence of a loading phase in rats trained to self-administer nicotine in 1-r daily sessions and the presence of a transient extinction burst.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".