Intravenous self‐administration of alcohol in rats—problems with translation to humans
Bibliographic record
Abstract
Alcohol is consumed orally by humans, and oral self-administration has been successfully modeled in laboratory animals. Over the last several years, attempts have been made to develop a procedure for the reliable intravenous (IV) self-administration of alcohol in rodents. IV self-administration would provide a better tool for investigating neurobiological mechanisms of alcohol reinforcement and dependence because confounding factors associated with oral self-administration, such as variations in orosensory sensitivity to alcohol and/or its absorption, are avoided. A review of the literature shows that rats, mice and non-human primates can initiate and maintain IV self-administration of alcohol. However, there are 50- to 100-fold interspecies differences in the reported alcohol infusion doses required. Most surprising is that the infusion dose (1-2 mg/kg) that reliably maintains IV alcohol self-administration in rats results in total alcohol intakes of only 20-25 mg/kg/hour, which are unlikely to have significant pharmacological effects. The evidence to support IV self-administration of such low doses of alcohol in rats as well as the potential biological mechanisms underlying such self-administration are discussed. The minute amounts of alcohol shown to reliably maintain IV self-administration behavior in rats challenge the relationship between their blood alcohol levels and the rewarding and reinforcing effects of alcohol.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".