ICES Working Group on Grey Seals Report of the First Meeting
Bibliographic record
Abstract
Damage to fisheries by the Grey seal, Halichoerus grypus, has been a serious problem in the UK and Canada for a number of years. The recent local increases in the abundance of the Grey seal in Norway, with an apparently related increase in fishery damage is seen as a problem which could become widespread if not checked in the near future. In order to give greater consideration to the ' problems associated with increases in stock size, an ICES Working Group was set up (C Res. 1976/2:15) to " •••• review the current status and trends in stock sizes, methodological problems of censusing and factors responsible, for the present expansion of the species. Data on the effects on fish resources, including cod worm and gear damage, should be collected 'and their economic implication considered. The ultimate aim of the Working Group should be to find feasible solutions to this complex problem ,•••• ". The Working Group (see Annex 1), met in Cambridge, UK, from 16-20 May 1977, and the agenda of that, meeting is appended as Annex 2."
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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 | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.016 |
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".