Associative learning in male rusty crayfish (<i>Orconectes rusticus</i>): conditioned behavioural response to an egg cue from walleye (<i>Sander vitreus</i>)
Bibliographic record
Abstract
Chemical communication governs a diversity of life processes in aquatic organisms. Crayfish use chemoreception during reproduction, social hierarchy formation, predation avoidance, and resource localization. Fish eggs release recognizable chemoattractants for vertebrate predators of eggs that can motivate crayfish to engage in egg predation as well. We hypothesized that male rusty crayfish ( Orconectes rusticus (Girard, 1852)) from a lake free of walleye ( Sander vitreus (Mitchill, 1818)) would not possess an innate recognition of a walleye egg cue. However, if conditioned by employing a single 2 h paired stimulus exposure (known food cue + egg cue), then male rusty crayfish would be attracted to the same egg cue upon subsequent exposure. Using a Y-maze behavioural arena we discovered that once conditioned, crayfish took significantly less time to choose the arm containing the egg cue alone relative to a control. Our study suggests that male rusty crayfish exhibit second-order conditioning through associative learning, allowing them to quickly and easily learn to identify novel odour stimuli from fish eggs under laboratory conditions.
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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".