Comparing memory-forming capabilities between laboratory-reared and wild<i>Lymnaea</i>: learning in the wild, a heritable component of snail memory
Bibliographic record
Abstract
We set out to determine whether the ability to form long-term memory (LTM) is influenced by laboratory rearing. We investigated the ability of four populations of Lymnaea stagnalis to form LTM following operant conditioning both in the freely behaving animal and at the electrophysiological level in a neuron, RPeD1, which is a necessary site for LTM. We hypothesized that laboratory rearing results in a decreased ability to form LTM because rearing does not occur in an 'enriched environment'. Of the four populations examined, two were collected in the wild and two were reared in the laboratory--specifically, (1) wild Dutch snails; (2) their laboratory-reared offspring; (3) wild Southern Alberta snails (Belly); and (4) their laboratory-reared offspring. We found that Belly snails had an enhanced capability of forming LTM compared with Dutch laboratory-reared snails. That is, the Belly snails, which are much darker in colour than laboratory-reared snails (i.e. blonds), were 'smarter'. However, when we tested the offspring of Belly snails reared in the laboratory we found that these snails still had the enhanced ability to form LTM, even though they were now just as 'blond' as their laboratory-reared Dutch cousins. Finally, we collected wild Dutch snails, which are also dark, and found that their ability to form LTM was not different to that of their laboratory-reared offspring. Thus, our hypothesis was not proved. Rather, we now hypothesize that there are strain differences between the Belly and Dutch snails, irrespective of whether they are reared in the wild or in the laboratory.
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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".