MétaCan
Menu
Back to cohort
Record W7034236475

The status of redfish (S. mentella and S. fasciatus) in Divisions 3LN at present and the likelihood its follow up in the near future (under the ongoing the Management Strategy or a status quo TAC scenario)

2018· other· en· W7034236475 on OpenAlexaboutno aff

Bibliographic record

VenueDIGITAL.CSIC (Spanish National Research Council (CSIC)) · 2018
Typeother
Languageen
FieldMedicine
TopicSARS-CoV-2 detection and testing
Canadian institutionsnot available
FundersUniversity of Cape TownEuropean CommissionDartmouth College
KeywordsStock (firearms)Stock assessmentResidualManagement strategyLogistic regressionMaximum sustainable yield
DOInot available

Abstract

fetched live from OpenAlex

There are two species of redfish in Divisions 3L and 3N, the deep-sea redfish (Sebastes mentella) and\nthe Acadian redfish (Sebastes fasciatus) that have been commercially fished and reported collectively as\nredfish in fishery statistics. Both species, occurring on Div. 3LN and managed as a single stock, don’t belong to\nisolated local populations but, on the contrary, are part of a large Northwest Atlantic complex ranging from\nthe Gulf of Maine to south of Baffin Island.\nThe ASPIC assessment of this stock is based on the logistic form of a non-equilibrium surplus\nproduction model (Schaeffer, 1954; Prager, 1994), adjusted to a standardized catch rate series (Power, 1997)\nand to all stratified-random bottom trawl surveys conducted in various years and seasons in Div. 3L and Div.\n3N from 1978 onwards. Both CPUE and surveys were used with all observations within each series.\nThe 2018 assessment proceed on the threshold of the new 2014 approach, the main features of the\nprevious input framework were kept, with MSY fixed at 1960-1985 average catch and the rest of the\napproved 2014 assessment framework updated. Despite its poor performance the 3L Spanish survey has\nbeen kept in the analysis due to its high correlation with the autumn 3LN Canadian survey, one of the two\nbackbone series of the assessment.\nASPIC results confirm a stable stock from the 1960’s to the first half of the 1980’s, sustaining an\naverage yield of 21 000t. Stock declined with a sudden rise of the catch over the late 1980’s first half of the\n1990’s, and started to gradually recover after catches fell to a residual level when the stock collapse. The\nmaximum observed sustainable yield (MSY) of 21 000 t can be a long term sustainable yield if fishing\nmortality stands at 0.11/year, exploiting a correspondent Bmsy at 187 000 t.\nFrom assessment results there is a high probability (CL’s 80%) that the stock was at the beginning of\n2018 above Bmsy, after crossing 2017 under a fishing mortality most likely below 34% Fmsy.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.737
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.114
GPT teacher head0.356
Teacher spread0.241 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueDIGITAL.CSIC (Spanish National Research Council (CSIC))Same topicSARS-CoV-2 detection and testingFrench-language works237,207