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Record W7133287648

Southern Gulf of St. Lawrence, NAFO Division 4T, White Hake (Urophycis tenuis) : stock assessment to 2022 and rebuilding plan scientific requirements

2025· other· en· W7133287648 on OpenAlexaffabout
François Turcotte, Daniel Ricard, Jenni L. McDermid, Jolene T. Sutton, François‐Étienne Sylvain

Bibliographic record

VenueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsGovernment of CanadaFisheries and Oceans Canada
Fundersnot available
KeywordsStock (firearms)FishingHakeStock assessmentPopulationFish stock
DOInot available

Abstract

fetched live from OpenAlex

The White Hake (Urophycis tenuis) stock in the southern Gulf of St. Lawrence (sGSL) is below its limit reference point (LRP) and in the Critical Zone of the Precautionary Approach (PA). The new Fish Stocks Provisions and the amended Fisheries Act legally require Fisheries and Oceans Canada (DFO) to develop a rebuilding plan for this stock. The sGSL stock assessment was updated using data up to 2022. The spawning stock biomass (SSB) in 2022 was 6.1 kilotonnes and the stock was in the Critical Zone of the PA. Fishing mortality of sGSL Hake ages 6+ has been below 0.02 since 2018. A review of the biomass reference points generated a new LRP based on a proxy for BMSY using the statistical catch-at-age model. With this new LRP, the stock is now estimated to have declined into the Critical Zone in 1992. Upper Stock and Target Reference points based on the proxy for BMSY were also calculated. In addition to the stock having a 75% probability of being at or above the LRP, the rebuilding target should include that the stock must be at or above this level for 5 consecutive years, and population projections must show the stock is likely to continue its positive trajectory under harvest for 5 years after the rebuilt state has been achieved. Population projections showed that the stock is unlikely to rebuild to the rebuilding target under prevailing conditions, even in the absence of fishing mortality. For the stock to rebuild, simulations showed that important reductions in natural mortality where necessary. Simulations also showed that the stock is highly vulnerable to declines in recruitment rates. Projections showed that at 100 tonnes (t) and 1,000 t of bycatch, SSB in 10 years would be reduced by 3.3% and 17.6% compared to no fishing, respectively. Preliminary analyses suggests the stock structure should be further investigated as Hake life history parameters in the St. Lawrence Estuary are more similar to Hake outside the sGSL. Additional measurable objectives for the rebuilding plan should include to increase the proportion of larger Hake and Hake aged 5+ to averages observed historically, to observe a return of Hake to their inshore spawning grounds, as well as an overall return of Hake to the inshore waters of the sGSL during the summer where they were historically distributed, to maintain the high recruitment observed in recent years and making enhanced efforts to understand the causes of the current high recruitment rates and how to promote it until the age structure has recovered, and finally to monitor discards and bycatch in fisheries intercepting White Hake more closely. Rebuilding progress will be tracked using the interim indicator derived from an annual survey and from stock assessment models. The periodic review of the rebuilding plan should be set to the 5-year stock assessment cycle with an interim update at the halfway point.

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)0.005
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.451
Threshold uncertainty score0.907

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.013
GPT teacher head0.262
Teacher spread0.249 · 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
GenreOther

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 routes2
Has abstractyes

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