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Record W2587427190 · doi:10.7717/peerj.2953

Will you swim into my parlour?<i>In situ</i>observations of Atlantic cod (<i>Gadus morhua</i>) interactions with baited pots, with implications for gear design

2017· article· en· W2587427190 on OpenAlexafffundabout
Phillip Meintzer, Philip Walsh, Brett Favaro

Bibliographic record

VenuePeerJ · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsMemorial University of Newfoundland
FundersFisheries and Oceans Canada
KeywordsGadusAtlantic codFishingFisheryEnvironmental scienceGadidaeUnderwaterOceanographyMarine engineeringFish <Actinopterygii>BiologyEngineeringGeology

Abstract

fetched live from OpenAlex

) in Newfoundland and Labrador, Canada. Pots produce lower environmental impacts than many other fishing gears, but they will only be a viable fishing strategy if they are efficient and selective at catching their target species. To study the behaviour of cod in and around pots, and how those behaviours affect pot efficiency, we used long-duration underwater video cameras to assess two models of cod pot deployed in the nearshore waters of Fogo Island, NL. We examined the number of cod that approached the pot, the number and proportion that successfully completed entries into the pot openings, and the number that exited, and related these factors to the direction of water movement. We observed very few entry attempts relative to the number of approaches by cod, and only 22% of all entry attempts were successful. We observed that 50% of approaches, 70% of entry attempts, and 73% of successful entrances occurred against the current, and 25% of cod were able to exit the pot following capture. Based on our observations, we suggest that future cod pots should have a greater number of entrances, or a mechanism to ensure that entrances rotate in line with the current, in order to maximize their catch efficiency for cod.

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 score0.062
Threshold uncertainty score0.658

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.047
GPT teacher head0.292
Teacher spread0.245 · 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

Citations25
Published2017
Admission routes3
Has abstractyes

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