Relationship between the grades of a learned aversive-feeding response and the dopamine contents in<i>Lymnaea</i>
Bibliographic record
Abstract
The pond snail Lymnaea learns conditioned taste aversion (CTA) and remembers not to respond to food substances that initially cause a feeding response. The possible relationship between how well snails learn to follow taste-aversion training and brain dopamine contents is not known. We examined this relationship and found the following: first, snails in the act of eating just before the commencement of CTA training were poor learners and had the highest dopamine contents in the brain; second, snails which had an ad libitum access to food, but were not eating just before training, were average learners and had lower dopamine contents; third, snails food-deprived for one day before training were the best learners and had significantly lower contents of dopamine compared to the previous two cohorts. There was a negative correlation between the CTA grades and the brain dopamine contents in these three cohorts. Fourth, snails food-deprived for five days before training were poor learners and had higher dopamine contents. Thus, severe hunger increased the dopamine content in the brain. Because dopamine functions as a reward transmitter, CTA in the severely deprived snails (i.e. the fourth cohort) was thought to be mitigated by a high dopamine content.
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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".