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Record W7133270467

Analyse de la pêche comparative à Terre-Neuve-et-Labrador – NM Calvert

2025· other· fr· W7133270467 on OpenAlexaboutno aff
Pêches et Océans Canada, Fisheries and Oceans Canada

Bibliographic record

VenueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada · 2025
Typeother
Languagefr
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCost analysisPower consumptionEconomic analysis
DOInot available

Abstract

fetched live from OpenAlex

Une pêche comparative a été effectuée aux printemps 2023 et 2024 afin de comparer le navire à moteur (NM) Calvert et le navire de la Garde côtière canadienne (NGCC) John Cabot. Les facteurs de conversion estimés s’appliquent directement aux navires jumeaux NGCC John Cabot et NGCC Capt. Jacques Cartier dans les divisions 3LNO de l’Organisation des pêches de l’Atlantique Nord-Ouest (OPANO), au printemps. Des facteurs de conversion sont requis pour sept taxons, dont aucun n’a présenté d’effet important de la longueur. Pour vingt-six taxons, aucune différence significative de capturabilité relative n’a été observée. Pour tous les autres taxons, il n’y avait pas suffisamment de données pour déterminer si un facteur de conversion était approprié. Afin d’appuyer les analyses au niveau des communautés, une analyse des facteurs de conversion a été effectué pour les groupes fonctionnels à l’échelle des unités de production écosystémique pour le Grand Banc (divisions 3LNO de l’OPANO). Aucune différence de capturabilité n’a été constatée entre les groupes fonctionnels.

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 score0.761
Threshold uncertainty score0.476

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.011
GPT teacher head0.276
Teacher spread0.265 · 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
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