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Record W7133275018

Assessment of the northern contingent of Atlantic Mackerel (Scomber scombrus) in 2020

2022· other· en· W7133275018 on OpenAlexaffabout
Andrew D. Smith, Linda Girard, Mélanie Boudreau, Elisabeth Van Beveren, Stéphane Plourde

Bibliographic record

VenueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsGovernment of CanadaFisheries and Oceans Canada
Fundersnot available
KeywordsStock assessmentFishingStock (firearms)Fish stockMackerel
DOInot available

Abstract

fetched live from OpenAlex

The status of the northern contingent of Atlantic mackerel (Scomber scombrus) in the Northwest Atlantic is assessed every two years using an age-structured stock assessment model. This document presents the background information, data, and methods used to calculate the main stock status indicators for mackerel which form the basis of advice given to the Fisheries and Aquaculture Management Branch of Fisheries and Oceans Canada (DFO) in the setting of Total Allowable Catch (TAC). The present stock assessment took place on the 25-26 of February and March 3rd of 2021 and provides advice for the 2021-2022 fishing seasons. The main results of this assessment indicated that in 2020, the spawning stock biomass (SSB) of mackerel was estimated to be at an all-time low and in the Critical Zone, as per DFO’s Precautionary Approach (PA), since 2011. Recruitment of age 1 fish was estimated to be near record lows in recent years and the age structure of the stock was severely truncated. The fishing mortality rate (F) was also above the reference point. Short-term projections indicated that the probability of the SSB leaving the Critical Zone by 2023 varied from 29%-37% (TAC = 10 000 t) to 51%- 58% (TAC = 0 t) depending on the assumptions of future recruitment.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.725
Threshold uncertainty score0.548

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.239
Teacher spread0.232 · 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 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

Citations0
Published2022
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