Baltic International Fish Survey Working Group (WGBIFS)
Bibliographic record
Abstract
The Baltic International Fish Survey Working Group (WGBIFS) plans, coordinates, and implements 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 compiles results from these surveys and provides the herring, sprat, cod and flatfish abundance indices for the Baltic Fisheries Assessment Working Group (WGBFAS) to use as tuning fleets.In 2025, WGBIFS completed the following tasks: (1) compiled survey results from 2024 and the first quarter of 2025; (2) planned and coordinated all surveys for the second half of 2025 and the first quarter of 2026, relevant to the assessments of the Baltic fish stocks. Data collected during the recent BITS surveys was added to the ICES Database of Trawl Surveys (DATRAS). Also, the Tow-Database was corrected and updated accordingly. 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 materials to DATRAS.The area coverage and the number of control hauls in the BASS, BIAS and GRAHS in 2024 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 2024 and 1st quarter 2025 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 survey standard deviation for Central Baltic herring acoustic index was calculated To improve transparency and reproducibility, WGBIFS has launched a multi-year initiative to review acoustic methodologies and scrutinization practices, laying the groundwork for even further TAF improvements, as well as enhanced reproducibility and consistency.Issues related to the data quality of demersal trawl surveys were discussed. The group agreed on conducting several experiments in Q4 2025 and Q1 2026 BITS, including a reduction of hauling time, changes in stomach sampling, sampling of Benthic fauna and adjustments in the haul allocations.Information on how different countries are handling the closed areas (offshore wind power plants and marine protected areas), that are restricted for scientific vessels to conduct the surveys, was gathered. The group agreed to feedback in a more standardized way using feedback sheets for the upcoming BITS.Survey manuals were reviewed, resulting in a number of implemented revisions and clarifications.Inquiries from other ICES expert groups were discussed and addressed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.009 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".