Strike Behavior and Behavioral Responses to Retrieval by Northern Pike ( <i>Esox lucius</i> ) During Ice Angling
Bibliographic record
Abstract
ABSTRACT Behavior of fish during catch and release has not been well studied despite its potential importance for fish conservation and welfare. We used underwater video footage to examine behaviors of ice‐angled northern pike ( Esox lucius ) during approach and retrieval. Initial approach behavior by pike appeared to involve assessment of the dead bait presented prior to striking. Based on 42 recorded captures, pike responded to hook set and retrieval with the common behaviors of thrashing, dashing, or rolling in the line. The use of different hook styles (treble vs. 0° offset circle hooks) generally did not alter most aspects of the behavioral response; however, pike rolled in the line for significantly longer periods of time when captured on double treble quick‐strike rigs. Rolling in the line complicates retrieval and causes fish injury. In addition, placement of the hook in the jaw of pike reduced the proportion of time spent dashing compared to external embedment. Ultimately, our study provides new insight into fish behavior and suggests that tackle and hook placement may have an important influence on how fish respond to being captured. Underwater video footage provides a potentially powerful tool for understanding how fish respond to angling and should be combined with other indicators of catch and release success to help develop fishery‐specific guidelines.
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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".