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Record W4372278986 · doi:10.2960/j.v54.m739

Contemporary analyses of comparative fishing data: a case study of Thorny skate on the Grand Banks (NAFO Divisions 3LNOP)

2023· article· en· W4372278986 on OpenAlexafffund
Noel G. Cadigan, Mark Simpson

Bibliographic record

VenueJournal of Northwest Atlantic Fishery Science · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsFisheries and Oceans CanadaMemorial University of Newfoundland
FundersCanada First Research Excellence FundFisheries and Oceans CanadaOcean Frontier Institute
KeywordsSkateGroundfishFishingFisheryDemersal zoneOtterStock assessmentBycatchStatisticsFisheries managementBiologyMathematics

Abstract

fetched live from OpenAlex

We re-analyze Thorny skate data from two comparative fishing experiments conducted by DFO in 1995 and 1996 using improved and more contemporary methods to estimate the relative efficiency of the Campelen 1800 demersal shrimp trawl survey protocol compared to the Engel 145 otter trawl. We correct possible bias in the method previously applied to these data. We investigate if there are size-based differences and if depth or spatial regions have important effects on results. We also investigate the influence and robustness of the estimation procedures, which was a concern in the original analyses of these data for other groundfish species. We did not find strong evidence that the relative efficiency of the Campelen trawl protocol compared to the Engel was different for smaller-sized Thorny skate compared to larger ones. However, we conclude that there is a potential that size-based differential catchability existed but there is insufficient information to reliably estimate these effects for Thorny skate. We also found evidence of significant differences in relative efficiency among NAFO Divisions and experiments, which is similar to other flatfish species. However, the mechanisms for these differences are unknown and it is not clear if spatial estimates should be used when converting Engel indices to Campelen equivalents. Hence, we do not recommend a different Engel-Campelen conversion factor than the one currently used in stock assessments for Thorny skates on the Grand Banks (NAFO Divisions 3LNOPs).

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.010
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.000
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 head0.225
GPT teacher head0.392
Teacher spread0.167 · 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.

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

Citations2
Published2023
Admission routes2
Has abstractyes

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