Practice in Aquaculture to Address Impacts on Wild Salmon Stocks
Bibliographic record
Abstract
meeting, welcomed members of the Task Force to Boston and thanked Fisheries and Oceans Canada for hosting the meeting. Ms Colligan noted that while the Task Force had a significant challenge before it, there was an excellent basis on which to build including NASCO’s Williamsburg Resolution, that had been developed in consultation with the industry, and the outcomes of the three international symposia co-convened by NASCO and ICES. The last symposium held in Bergen in 2005 had concluded that cultured salmon could have significant negative impacts on wild salmon and that while there had been considerable progress in addressing these impacts further action was needed, particularly in relation to sea lice and escapes, in order to safeguard the wild stocks. The Bergen symposium had also highlighted research requirements in relation to impacts of aquaculture on the wild stocks. She indicated that the role of the Task Force would be to review existing guidelines and standards to address impacts of aquaculture on the wild stocks and to identify those measures that are considered to be most effective in addressing impacts, what information is available to evaluate their effectiveness and the additional measures that may be needed to safeguard the wild stocks. Dr Webster referred to the progress made to date through the NASCO/ISFA Liaison Group and the need to make further progress to address the remaining challenges. He indicated that the industry had prepared a compilation of legislation and Codes of Practice to inform the work of the
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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 | 0.035 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".