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Effects of different angling practices on post‐release behaviour of nest‐guarding male black bass, <i>Micropterus</i> spp.

2007· article· en· W2077685318 on OpenAlexafffund
K. C. Hanson, Steven J. Cooke, Cory D. Suski, David P. Philipp

Bibliographic record

VenueFisheries Management and Ecology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsMinistry of the Environment, Conservation and ParksCarleton University
FundersMinistry of Natural ResourcesIllinois Department of Natural Resources
KeywordsMicropterusBass (fish)PredationFisheryFishingNest (protein structural motif)BiologyCatch and releaseEcologyRecreational fishing

Abstract

fetched live from OpenAlex

Abstract This study evaluated how different angling practices affect the short‐term post‐release behaviour of nest‐guarding male black bass, Micropterus spp. Male largemouth bass, M. salmoides (Lacepède), and smallmouth bass, M. dolomieu (Lacepède), were angled from their nests and subjected to treatments designed to simulate a variety of common angling practices associated with catch‐and‐release angling, including fishing tournaments. In addition, some nests had broods reduced (removal of the majority of the eggs or fry from the nest) during the angling treatments to simulate predation of offspring during the angling event. Fish subjected to procedures simulating fishing tournaments (including a 1‐h livewell confinement and release 100 m from the nest) exhibited significantly longer rest periods prior to returning to their nest than did other treatment groups. This rest period was longer for largemouth bass than smallmouth bass. Brood removal and air exposure increased abandonment rates compared with controls. These results show that sublethal stressors inherent in some angling practices (such as air exposure and livewell confinement) may delay the return of male black bass to their nest. In the presence of nest predators, the delay in return time could result in increased nest abandonment.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.872

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.006
GPT teacher head0.205
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations51
Published2007
Admission routes2
Has abstractyes

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