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Record W4221081643 · doi:10.1139/cjfas-2021-0266

Northwest Atlantic redfish science priorities for managing an enigmatic species complex

2022· article· en· W4221081643 on OpenAlexafffundvenue
Noel G. Cadigan, Daniel E. Duplisea, Caroline Senay, Geneviève J. Parent, Paul D. Winger, Brian C. Linton, Kristján Kristinsson

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsFisheries and Oceans CanadaMemorial University of Newfoundland
FundersFisheries and Oceans CanadaCanada First Research Excellence FundMemorial University of NewfoundlandPinngortitaleriffik
KeywordsSebastesFisheryFishingGroundfishStock assessmentGeographyFisheries managementBiologyEcologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Redfish ( Sebastes spp.) in the Northwest Atlantic (NWA) extend from Baffin Island in the north to the Gulf of Maine in the south. The two most abundant species are Sebastes mentella and Sebastes fasciatus, which are morphometrically similar and difficult to visually distinguish. Redfish are long-lived, slow-growing, late-maturing, tend to produce large year classes episodically, and have complex population structure. Intraspecific genetic groups are abundant in the NWA. They are often semipelagic and patchily distributed, which makes them difficult to survey. These are all characteristics that cause difficulties for stock assessment and for sustainable fisheries management. This was the focus of The Ocean Frontier Institute Northwest Atlantic Redfish Symposium in 2018. In this paper, we synthesize the information known about NWA redfish. To improve the scientific basis for sustainable harvest strategies, key research recommendations involve (1) improved biological sampling including species and ecotype; (2) developing integrated stock assessment models; (3) developing harvest strategies with management reference points that are appropriate for redfish; (4) improving fishing technology and practices to avoid capture of small nonmarketable redfish and other species.

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)0.008
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.880
Threshold uncertainty score0.239

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0050.004
Open science0.0020.005
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0100.002

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 head0.041
GPT teacher head0.250
Teacher spread0.209 · 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 designTheoretical or conceptual
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

Citations16
Published2022
Admission routes3
Has abstractyes

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