Strain transformation: Enhancement of invertebrate memory in a new rearing environment
Bibliographic record
Abstract
Memory formation is influenced by a variety of factors, including the environmental conditions in which an organism is reared. Here, we studied the memory-forming ability of the lab-bred B-strain of Lymnaea following a change in their rearing environment from Brock University to the University of Calgary. We have previously demonstrated that this move enhances memory-forming ability and here we studied the magnitude of this phenotypic change. Once reared to adulthood at the University of Calgary, the B-strain animals were first tested to determine how many training sessions were required for the formation of long-term memory (LTM) to occur. Following this change in environment, the B-strain transformed into a ‘smart’ lab-bred strain requiring only a single 0.5 h session to form LTM. Next, we tested whether exposure to physiologically relevant stressors would block the formation of LTM in this ‘transformed’ B-strain, as this obstruction has previously been observed in ‘smart’ snails collected from the wild. Interestingly, neither stressor tested in this study perturbed memory formation in this ‘transformed’ lab-bred strain. Additionally, both the ‘smart’ memory phenotype, as well as the increased stress resiliency, were observed in the second generation of ‘transformed’ B-strain at both the juvenile and adult stages. This suggests that a change in rearing environment can contribute to the memory-forming ability of lab-bred Lymnaea.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".