Chemically mediated learning in juvenile rainbow trout. Does predator odour pH influence intensity and retention of acquired predator recognition?
Bibliographic record
Abstract
The prediction that variability in ambient pH will influence the intensity and retention of learned predator recognition in juvenile rainbow troutOncorhynchus mykisswas tested under laboratory conditions. Juvenile rainbow trout were conditioned to recognize the odour of a novel predator at pH 6·0 or 7·0 and then tested for learned recognition of the predator odour at pH 6·0 or 7·0 at 2 or 7 days post‐conditioning. When tested 2 days post‐conditioning, rainbow trout exhibited a significant learned antipredator response regardless of predator odour pH. The response was stronger, however, when the test pH matched the conditioning pH. When tested 7 days post‐conditioning, rainbow trout only exhibited a learned response when conditioning and testing pH were the same. These results demonstrate that episodic acidification may impair the strength and retention of acquired predator recognition learning. Given the demonstrated survival benefits associated with learned predator recognition in prey fishes, such impairment will probably have considerable negative impacts at both individual and population levels.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".