Report of the Working Group on Fishery Statistics Liaison (WGSTAL)
Bibliographic record
Abstract
The WGSTAL meeting was held back‐to‐back to the Eurostat Working Group meet‐ing on Fishery statistics 28–29 April 2008. The Eurostat meeting included a number of agenda points that also are relevant to ICES and this report should be consulted. Par‐ticipation in the WGSTAL and the REuirostat meeting is the same. ICES has conducted this review over the last three years with David Cross (former Eurostat) as consultant. David Cross presented the results. The background for the project is the need for long time‐series useful for discussing general changes in biodi‐versity and distribution of species. E.g. fisheries data have proven very useful in dis‐cussions related to effects of climate change. The review is based on data published in Bulletin Statistique (ICES), original submis‐sions and consideration of having consistent time‐series. In particular, there had been submissions after the annual publication of Bull. Stat. and these submissions are in‐cluded in the revised dataseries. The review is now concluded, it was possible to cor‐rect a number of problems for the period 1950–2005 whereas data before that time are sparse and also collected less systematically. It was therefore decided that data for the first half of the century up to 1949 (incl.) would not be scrutinised and potentially amended but would be converted to electronic form assuring that the transfer is accu‐rate. The project has benefited from earlier work done by Reg Watson (Univ. BC, Canada) and David Cross was grateful that these database had been made available to ICES. David Cross noted that the results from a previous project on discrepancies between databases held by NAFO, ICES/Eurostat, ICCAT, and FAO had been very helpful. There are still discrepancies between the revised ICES/Eurostat data and the totals for FAO area 27 that are held by FAO. Some of these discrepancies are as a consequence of area redefinitions after the publication of the data. ICES has revised its data cor‐recting for such redefinitions. The area redefinitions concerned the Northwest Atlan‐tic (which for the earliest part of the series was included in the ICES data) and certain areas in what is to‐day the CECAF area. These discrepancies will be discussed with FAO at a later stage. The status of the project is that revision of the dataseries is completed; data from the period 1950–2005 have been revised as appropriate, the national correspondents have been asked to consider the first part of the dataseries (1950–1972) and that the second part of the time‐series will be mailed to the national statistical correspondents before summer for their comments.
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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 | 0.038 | 0.052 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.066 | 0.059 |
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".