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Record W2889031422 · doi:10.22621/cfn.v132i1.2040

Observations of Mudpuppy (<i>Necturus maculosus</i>) bycatch in a recreational ice fishery in northern Ontario

2018· article· en· W2889031422 on OpenAlexafffundvenueabout
Robert J. Lennox, William M. Twardek, Steven J. Cooke

Bibliographic record

VenueThe Canadian Field-Naturalist · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsCarleton University
FundersOntario Ministry of Natural Resources and ForestryMinistry of Natural Resources
KeywordsBycatchHookFisheryFishingRecreationRecreational fishingSalamanderCatch and releaseBiologyEcology

Abstract

fetched live from OpenAlex

Bycatch in fisheries is a well-explored topic, although less so in recreational fisheries. We encountered frequent bycatch of Mudpuppy (Necturus maculosus), a neotenic aquatic salamander that is active in winter, in passively baited ice-fishing gear targetting teleost fishes. We noted hook location in Mudpuppies captured by two hook types: J-hooks and circle hooks. Our prediction was that circle hooks would reduce the frequency of deep hooking of Mudpuppies, which is often cited as an important predictor of post-release mortality in fishes. We found no difference in the frequency of deep hooking of Mudpuppies captured by circle or J-hooks, although, in a subset of Mudpuppies (n = 13) held for 24 h after capture, one death occurred (8%). Further research may be necessary to determine whether deeply hooked Mudpuppies can pass or shed hooks and survive beyond the 24-h period we monitored. However, our findings suggest that anglers and managers should consider refinements to handling practices for Mudpuppies captured as bycatch, because they are likely to survive if handled cautiously. These results, which are among the first describing non-fish bycatch in recreational fisheries, call for managers and anglers who encounter Mudpuppies during recreational fishing to seek more information and educational opportunities to improve the fate of this important component of temperate freshwater ecosystems and ecological indicator speciesthat is incidentally captured by ice fishing.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.328
Threshold uncertainty score0.660

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
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 head0.017
GPT teacher head0.213
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2018
Admission routes4
Has abstractyes

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