Salmon at Sea: Scientific Advances and their Implications for Management: an introduction
Bibliographic record
Abstract
Abstract Hansen, L. P., Hutchinson, P., Reddin, D. G., and Windsor, M. L. 2012. Salmon at Sea: Scientific Advances and their Implications for Management: an introduction. – ICES Journal of Marine Science, 69: 1533–1537. Concerns about increased mortality of salmon at sea resulted in the development and implementation of a major internationally coordinated, public- and privately funded programme of research, the SALSEA programme. Major research surveys were conducted in the Northeast and Northwest Atlantic in 2008 and 2009, and there was enhanced sampling of the Atlantic salmon (Salmo salar) fishery at West Greenland. The findings from these surveys and sampling programmes, and from important new analyses of historical data, stable isotope and genetic stock assignment studies, recent tagging experiments, and other research, were reviewed at an international symposium organized by North Atlantic Salmon Conservation Organization and ICES and held in La Rochelle, France, 11–13 October 2011. This well-attended symposium, entitled “Salmon at Sea: Scientific Advances and their Implications for Management”, highlighted advances in our understanding of the migration, distribution, and survival of salmon at sea, possible causes of the recent increased mortality, future research priorities, and the management actions that might be undertaken to mitigate the increased mortality of salmon at sea.
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.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.006 |
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".