Effects of behavioral strategies on catchability, bait selectivity, and hunting behavior in northern pike (<i>Esox lucius</i>)
Bibliographic record
Abstract
This study investigated how northern pike with two behavioral strategies in the context of predation interact with natural and artificial baits in simulated angling experiments. Predator types were assessed in three behavioral trials over 15 days by measuring foraging latency under altered conditions (abruptly increased light intensity). Latency revealed fast and slow predator responses showing high individual repeatability, interpreted as proactive and reactive predator types, with reactive individuals adapting their response over time. Both types displayed similar hunting performances in predation trials with live prey under habituated conditions. In angling trials, proactive pike expressed significantly more predation than reactive pike, independent of bait type. During angling trials, predator type did not affect bait handling, while both predator types developed strong sequential bait avoidance, indicating a learning effect. Angling trials did not affect hunting for live prey. The results suggest that pike exhibit individual differences in responses to environmental changes linked to their predatory behavior. Angling selection may play a role in pike populations, with the proactive predator type more likely to be hooked than the reactive type.
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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 | 0.001 |
| 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".