MétaCan
Menu
Back to cohort
Record W3090773774 · doi:10.1016/j.aaf.2020.09.005

Comparing the size selectivity of a novel T90 mesh codend to two conventional codends in the northern shrimp (Pandalus borealis) trawl fishery

2020· article· en· W3090773774 on OpenAlexaff
Haraldur Arnar Einarsson, Zhaohai Cheng, Shannon M. Bayse, Bent Herrmann, Paul D. Winger

Bibliographic record

VenueAquaculture and Fisheries · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsShrimpFisheryBiologyBycatchEnvironmental scienceOceanographyFish <Actinopterygii>Geology

Abstract

fetched live from OpenAlex

The size selectivity and usability of three codends were quantified and compared for the first time in the inshore Northern shrimp (Pandalus borealis) trawl fishery of Iceland using the covered codend method: a conventional diamond-mesh codend (T0), conventional square-mesh codend (T45), and a 90° turned mesh codend (T90) constructed of four panels and with shortened lastridge ropes. Fishers, wanting to increase the average-individual size of captured shrimp, had requested the T90 codend to be compared with conventional codends for consideration in the fishery. Results showed that, on average, the T45 and T90 codends had better size selectivity than the T0 codend in terms of releasing individuals smaller than 13 mm carapace length (Minimum References Size; MRS). The T90 codend retained significantly less Northern shrimps between 9 and 19 mm than the T0 codend and between 15 and 19 mm than the T45 codend. No significant difference of size selectivity between T45 and T0 codends was observed. All three codends presented high retention ratios of Northern shrimps above MRS (>63%) for the population encountered. However, the T0 codend was not effective at sorting out small Northern shrimps; at least 86% of Northern shrimps smaller than 13 mm were retained in the T0 codend if encountered. Catches from T45 and T90 codends had a lower proportion of shrimp below MRS. Since discarding of undersized Northern shrimps is prohibited in Iceland and fishers wanted to catch on average larger shrimp, using the novel T90 codend would enable fishers to use their quotas more efficiently.

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)0.000
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 score0.259
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.259
Teacher spread0.224 · 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

Citations20
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueAquaculture and FisheriesSame topicMarine and fisheries researchFrench-language works237,207