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Record W7133279866

Results of comparative fishing between the Canadian Coast Guard Ship (CGSS) Teleost and CCGS John Cabot in the Newfoundland and Labrador Region in Spring 2023

2025· other· en· W7133279866 on OpenAlexaboutno aff
S. Trueman, E. Novaczek, K. Silver, L. Wheeland

Bibliographic record

VenueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCoast guardFishingSpring (device)SubdivisionTaxonFish <Actinopterygii>Census
DOInot available

Abstract

fetched live from OpenAlex

Comparative fishing has been ongoing since 2021 in the Newfoundland and Labrador Region as the multispecies survey transitions to new vessels, the Canadian Coast Guard Ship (CCGS) John Cabot and CCGS Capt. Jacques Cartier. This program aims to determine differences in relative catchability between the outgoing vessels using the Campelen trawl and the new vessels, using the modified Campelen trawl. Analysis of this program was considered in two CSAS Regional Peer Review meetings. This document presents analyses for the CCGS Teleost operating in spring based on paired tows completed in 2023. The CCGS Teleost is not a primary survey vessel in this region in spring but has been used to supplement or replace the CCGS Wilfred Templeman and CCGS Alfred Needler during the Campelen series. Comparative fishing data were sufficient to estimate conversions for 12 taxa and determine no conversion is required for 34 taxa for the CCGS Teleost spring time series. Additionally, three taxa were found to have insufficient data to estimate a conversion factor. Due to poor sampling coverage in Subdivision 3Ps, data were deemed representative for Northwest Atlantic Fishery Organization (NAFO) Divisions 3LNO only, with a few exceptions made for Subdivision 3Ps.

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)0.002
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 score0.088
Threshold uncertainty score0.177

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.255
Teacher spread0.236 · 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 Canada→French-language works237,207→