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Record W6925720445 · doi:10.17895/ices.pub.23675049

Baltic International Fish Survey Working Group (WGBIFS)

2023· report· en· W6925720445 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Council for the Exploration of the Sea (ICES) · 2023
Typereport
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsHerringBaltic seaSpratQuarter (Canadian coin)Demersal zoneFish stockDemersal fishFish <Actinopterygii>Table (database)

Abstract

fetched live from OpenAlex

The Baltic International Fish Survey Working Group (WGBIFS) plans, coordinates, and imple-ments demersal trawl surveys and hydroacoustic surveys in the Baltic Sea including the Baltic International Acoustic Survey (BIAS), the Baltic Acoustic Spring Survey (BASS), and the Baltic International Trawl Surveys (BITS) in the 1st and 4th quarter on an annual basis. The group com-piles results from these surveys and provides the herring, sprat, cod and flatfish abundance in-dices for the Baltic Fisheries Assessment Working Group (WGBFAS) to use as tuning fleets. In 2023, WGBIFS completed the following tasks: (1) compiled survey results from 2022 and the first half of 2023, (2) planned and coordinated all Baltic fish stocks assessment relevant surveys for the second half of 2023 and the first half of 2024, (3) updated the common survey manuals according to decisions made during the annual WGBIFS meeting. Data from the recent BITS was added to the ICES Database of Trawl Surveys (DATRAS). The Tow-Database was corrected and updated. The Access-databases for aggregated acoustic data and the ICES database of acoustic-trawl surveys for disaggregated data were updated. All countries registered collected litter ma-terials to DATRAS. The area coverage and the number of control hauls in the BASS, BIAS and GRAHS in 2022 were considered to be appropriate to the calculation of tuning indices and the data can be used for the assessment of Baltic herring and sprat stocks. The number of valid hauls accomplished during the 4th quarter 2022 and 1st quarter 2023 BITS were considered by the group as appropriate to tuning series and the data can be used for the assessment of Baltic and Kattegat cod and flatfish stocks. BIAS and BASS survey sampling variance calculation questions were discussed and standard deviation for Central Baltic herring acoustic index series calculated. In comparison exercises between the StoX survey computational method and traditional IBAS calculation methods it was found that the StoX project, developed for the WGBIFS, has small methodological differences compared to the standard calculation method used by the group, as specified in the Manual for the International Baltic Acoustic Surveys (IBAS), and is thereby caus-ing a small difference in the total number of herring and sprat., The work with transition to a more transparent calculation software (e.g. StoX) will continue during the next period with more thorough analysis of calculation methodologies. A further comparison exercise between the StoX method and traditional Gulf of Riga Herring Survey calculation method was performed using data from 11 last years. It showed no major differences in herring total abundance estimates for most of the years. However, notable differ-ences were in the age compositions of those two methods. Some errors and differences in input data (uploaded into the ICES database) were found and therefore the further analysis was post-poned until these issues are fixed. WGBIFS is planning to continue with analogical comparison exercises in the coming years before the final transition to a transparent reproducible pathway into the ICES Transparent Assessment Framework (TAF) can be done. Work towards transitioning to TAF will continue during the next 3-year period until all methodological and database differences are resolved. Inquiries from other ICES expert groups were discussed and addressed.

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.

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)0.006
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.782
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.583
GPT teacher head0.350
Teacher spread0.234 · 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