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Record W6961096523 · doi:10.14466/cefasdatahub.126

A data product derived from Northeast Atlantic groundfish data from scientific trawl surveys 1983-2020

2022· dataset· en· W6961096523 on OpenAlexaboutno aff

Bibliographic record

VenueCefas · 2022
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGene expression and cancer classification
Canadian institutionsnot available
Fundersnot available
KeywordsGroundfishFishingQuarter (Canadian coin)Sampling (signal processing)BayBycatchSurvey data collectionEnvironmental dataSurvey methodology

Abstract

fetched live from OpenAlex

This is a data product to support state indicators that are based from groundfish biological data, derived using primary data from surveys undertaken in the Northeast Atlantic between 1983 and 2020. Catch records by taxonomic group and by length category in terms of biomass and numbers of fish standardised to duration (per hour) or to the area swept by the haul. Data are available from multiple surveys using data downloaded from the ICES database of trawl surveys (DATRAS) once quality-controlled and standardised following procedures detailed in Greenstreet and Moriarty 2017. Data file names reflect the OSPAR region sampled, country conducting the sampling, fishing gear and time of years of sampling (as defined by Greenstreet and Moriarty 2017), e.g.: BBICFraBT4 refers to Bay of Biscay and Iberian Coast data from France by a Beam Trawl survey in quarter 4 of the year and GNSIntOT3 refers to Greater North Sea data from International (multiple countries) sampling by an Otter Trawl survey in quarter 3 of the year etc. Greenstreet, S.P.R. and Moriarty, M. (2017) OSPAR Interim Assessment 2107 Fish Indicator Data Manual (Relating to Version 2 of the Groundfish Survey Monitoring and Assessment Data Product). Scottish Marine and Freshwater Science Vol 8 No 17, 83pp. DOI: 10.7489/1985-1 Scientific survey data collected by multiple countries and made available through ICES DATRAS (https://www.ices.dk/data/data-portals/Pages/DATRAS.aspx). Swept-area estimates were generated by ICES 2021ab (ICES. 2021a. Workshop on the production of swept-area estimates for all hauls in DATRAS for biodiversity assessments (WKSAE-DATRAS). ICES Scientific Reports. 3:74. https://doi.org/10.17895/ices.pub.8232; ICES. 2021b. Workshop on the production of abundance estimates for sensitive species (WKABSENS); ICES Scientific Reports. 3:96. https://doi.org/10.17895/ices.pub.8299). ICES Data Centre host the database of trawl surveys (DATRAS) for groundfish and beam trawl data. DATRAS has an integrated quality check utility. All data, before entering the database, have to pass an extensive quality check. Despite this errors and missing data arise, which are subsequently dealt with by the data submitters from the contributing countries as required. However, this screening process was implemented in 2009 for data from 2004 onwards. Since some survey time-series extend back to the 1960s, historic data (unless re-evaluated and re-submitted by contributing countries) may not have been subject to the same level of quality control as these more recent data. Furthermore, the type of information collected, the level of detail and resolution in the data, has gradually evolved over time. In order to derive a single format, quality assured monitoring programme data product covering the entire Northeast Atlantic region inconsistencies in the datasets required resolution. These corrections are detailed in ICES 2021a,b: Biological data for trawl surveys are downloaded directly from DATRAS in raw exchange format (known as “HL data”). Ancillary data were processed by ICES 2021a,b to create the “SweptAreaAssessmentOutput” (which replaces the “HH data”) and these were downloaded from the same location: https://datras.ices.dk/Data_products/Download/Download_Data_public.aspx Data are processed to create a standalone data product to be used for indicator assessments of fish and elasmobranchs. Initially, hauls are subset to determine the Standard Monitoring Programme (i.e. excluding invalid hauls including those of duration shorter than 13 minutes or longer than 66 minutes, following Greenstreet and Moriarty 2017) and these hauls are used to define the Standard Survey Area by excluding areas sampled infrequently over time). Biological data were accepted with ICES SpecVal of 1, 4, 7, 10 (see http://vocab.ices.dk/ for further information on SpecVal categories). Additional QA/QC is made at this step to determine if species identification issues are present in the raw biological data and these were discussed and agreed with the Chief Scientist for each survey.

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)0.002
metaresearch head score (Gemma)0.008
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: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.231
Threshold uncertainty score0.460

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.012
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0440.027

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 head0.071
GPT teacher head0.300
Teacher spread0.229 · 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
GenreDataset

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

Citations3
Published2022
Admission routes1
Has abstractyes

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