Black tea differs from green tea: it suppresses long-term memory formation in<i>Lymnaea</i>
Bibliographic record
Abstract
Foods, such as Green tea (GT), containing the flavonol, (-)-Epicatechin (Epi), enhance the formation of long-term memory (LTM) when snails are operantly conditioned in that substance. That is, a single 0.5 h training session results in LTM; whereas similar training in pond water does not result in LTM. It was of interest to determine if Black tea (BT), which is a more popular beverage than GT and which is derived from the same tea leaves, also enhances LTM formation. We found that BT, unlike GT, depressed homeostatic aerial respiratory behaviour and obstructed LTM formation. We used two different methods to determine if BT altered LTM formation and both procedures showed us that BT obstructed LTM formation. We conclude that BT obstructs LTM formation and depresses homeostatic aerial respiration.
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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 | 0.000 |
| 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".