Ondansetron and Delta-9-Tetrahydrocannabinol Interfere With the Establishment of Lithium-Induced Conditioned Taste Avoidance in the House Musk Shrew (Suncus murinus).
Bibliographic record
Abstract
Considerable evidence suggests that rats can learn to avoid a taste in the absence of nausea. The current experiments evaluated the potential of the antiemetic agents, ondansetron (OND) and delta-9-tetrahydrocannabinol (THC), to interfere with lithium chloride (LiCl)-induced taste avoidance in the house musk shrew, Suncus murinus, an insectivore that, unlike rats, is capable of vomiting. At a dose that did not modify saccharin (Experiment 1) or sucrose (Experiment 2) intake, OND prevented the establishment of LiCl-induced taste avoidance in the shrew. A low dose of THC (1 mg/kg), which did not modify sucrose intake during conditioning, also prevented the establishment of LiCl-induced taste avoidance in the shrew. Higher doses of THC were also effective, but they also suppressed sucrose consumption during conditioning. These results suggest that nausea is a necessary component of the unconditioned stimulus for the establishment of conditioned taste avoidance in the shrew, unlike the rat, which does not vomit when injected with a toxin.
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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) | 0.001 | 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".