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Record W7133280547

Reference Points for Scallop Fishing Areas 25, 26, and 27B

2025· other· en· W7133280547 on OpenAlexfundno aff
Fisheries and Oceans Canada, Pêches et Océans Canada

Bibliographic record

VenueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersNational Oceanic and Atmospheric AdministrationNational Marine Fisheries ServiceDalhousie University
KeywordsMaximum sustainable yieldFishingStock (firearms)Biomass (ecology)Stock assessmentIndex (typography)
DOInot available

Abstract

fetched live from OpenAlex

The stock status indicator for scallop fishing areas (SFAs) 26C and 27B is the most recent three-year geometric mean of the fully-recruited survey biomass index for each area. The stock status indicator for SFAs 25A and 26A is the model estimated fully-recruited biomass for each area. Where available, model-based approaches were recommended over the survey biomass index-based approaches. Model-based approaches are preferred due to their ability to quantify uncertainty and changes in stock dynamics (productivity). Candidate reference points were considered based on modelled maximum sustainable yield (MSY) simulations for SFAs 25A and 26A. These simulations utilized the stock dynamics between 1994 and 2022. Using the model-based MSY simulations, limit reference points (LRP) were adopted for SFAs 25A at 1,160 tonnes and 26A at 2,000 tonnes; these LRPs correspond to BMSY(40) (40% of biomass at maximum sustainable yield). Candidate reference points were evaluated based on fully-recruited survey biomass index based proxies of BMSY and B0 (unfished biomass) for SFAs 26C and 27B. Using the index-based approaches, LRPs were adopted for SFAs 26C at 890 tonnes and 27B at 628 tonnes; these LRPs correspond to BMSY(30) (30% of biomass at maximum sustainable yield). Guidance was provided for the development of upper stock reference points (USRs) and removal references (RRs) in all areas. For each of SFAs 25A and 26A, a scenario was developed using harvest decision rule simulations to demonstrate how this method could quantify the impact of alternative management objectives.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.923
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.012
GPT teacher head0.247
Teacher spread0.235 · 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 designTheoretical or conceptual
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

Citations0
Published2025
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