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Record W7133270019

Review of the assessment framework for Atlantic Cod in NAFO 3Pn4RS : treatment of catch and individual weights, and other assessment model considerations

2024· other· en· W7133270019 on OpenAlexaboutno aff
Hugues P.‏ Benoît, Noel G. Cadigan, Jordan Ouellette-Plante, Claude Brassard

Bibliographic record

VenueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsStock assessmentStock (firearms)FishingImpact assessmentAtlantic codFisheries management
DOInot available

Abstract

fetched live from OpenAlex

In 2021, Fisheries and Oceans Canada’s Science Branch in the Quebec region initiated a review of the assessment framework for the stock of Atlantic Cod (Gadus morhua) in the northern Gulf of St. Lawrence (nGSL; NAFO Subdivision 3Pn and Divisions 4RS). The review was divided into two parts. The first part, which took place in the spring of 2021, reviewed key inputs to the stock assessment. The second part, which took place in May 2022, reviewed proposed analytical models for the nGSL cod stock and additional inputs to those models. This document presents some model inputs which were not reviewed in 2021, and the results of analyses that motivated some important considerations incorporated into the assessment model. First, we review modifications made to the fishery catch-at-age series and proposals for the definition and use of catch bounds in censored catch modelling incorporated into the revised assessment model. Second, we review and revise annual values for the beginning-of-year stock weights also used in the assessment model. Third, we review approaches incorporated into the assessment model to address changes in survey coverage which occurred in the past in two fishery-independent surveys. Fourth, we present evidence that particular calibration factors used to account for a change in vessel and gear in the research vessel survey series may be inadequate for young cod. This evidence motivated explicit estimation of relative catchability in the assessment model for these ages. Fifth, we present evidence for somewhat different trends displayed by groups of abundance indices included in the assessment model, and briefly discuss the possible causes and how these differences could be accounted for in assessment modelling. Finally, we briefly discuss published research findings which had not previously been incorporated into the assessment, but provide useful support in the modelling.

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)0.018
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.773
Threshold uncertainty score0.452

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.029
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0090.009
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0040.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.026
GPT teacher head0.309
Teacher spread0.283 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2024
Admission routes1
Has abstractyes

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Same venueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du CanadaFrench-language works237,207