Effects of Recreational Fishing Gear Type on Reflex Impairment and Post‐Release Swimming Activity of Smallmouth Bass
Bibliographic record
Abstract
ABSTRACT Recreational anglers have access to a diverse range of rod and line strengths that enable them to choose equipment that can enhance their ability to effectively target and capture specific fish of a given body size. However, anglers may not always select the appropriate gear type for the targeted species. Here, we assessed the effect of gear setup on immediate reflex impairment and short‐term post‐release swimming behavior of Smallmouth Bass (Micropterus dolomieu) for 10‐min. Smallmouth Bass were caught by angling in water temperatures of 22.7°C–26.2°C using ultralight or medium spinning gear. Fight times were longer for fish captured on ultralight gear than medium gear, and fight times were longer for larger fish. Generally, fight times > 18 s resulted in one or more immediate reflex impairments, while fish with fight times < 18 s had no immediate reflex impairments. Post‐release swimming activity was only influenced by gear type used. Upon release, Smallmouth Bass captured using ultralight gear spent more time sustained swimming than those caught using medium gear type that spent more time resting. Given that fight times were longer for Smallmouth Bass captured using ultralight gear, they were conceivably more exhausted. This increased post‐release swimming activity indicates that fish may need to engage in sustained swimming to facilitate physiological recovery. Our findings suggest that anglers should select gear types that minimize fight times to avoid reflex impairments and extended periods of post‐release sustained swimming needed for recovery.
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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) | 0.002 | 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".