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Record W7133287510

Rebuilding simulations for 3Ps cod

2023· other· en· W7133287510 on OpenAlexfundaboutno 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 · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersFisheries and Oceans Canada
KeywordsGadusStock (firearms)FishingAtlantic codTime horizonClimate change
DOInot available

Abstract

fetched live from OpenAlex

Atlantic cod Gadus morhua in NAFO Subdivision 3Ps remains well within the critical zone of Canada's Precautionary Approach (PA) Framework, and was at 48% of the Limit Reference Point (LRP) in 2021. Fisheries and Oceans Canada (DFO) has a legal requirement to develop a Rebuilding Plan for this stock. The 3Ps Atlantic cod stock is co-managed by Canada and France. ”MSE-lite” is a framework that uses closed-loop simulations of the assessment model to project the stock trajectory under a range of recruitment (R) and natural mortality (M) scenarios, and with the application of various management procedures. This framework is considered to be scientifically sound, and is adequate for assessing the rebuilding potential of Atlantic Cod in 3Ps in support of the development of a Rebuilding Plan for this stock. Scenarios of R and M tested within MSE-lite all fall within the conditions previously experienced by the stock. In a changing ocean climate these conditions may not adequately capture future conditions, and biological evidence suggests M is more likely to increase than decrease. The prevailing conditions defined for R and M are appropriate for calculating minimum time to rebuild to the proposed target in the absence of fishing (Tmin). The stock is expected to reach the proposed rebuilding target (above the LRP with a 75% probability) in 2036.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score0.389

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.015
GPT teacher head0.268
Teacher spread0.252 · 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 designSimulation or modeling
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
Published2023
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