Development of cod farming in Norway: Past and current biological and market status and future prospects and directions
Bibliographic record
Abstract
Abstract Atlantic cod is a historically abundant species in the North Atlantic region and has contributed to the prosperity of many nations. But a decline in stocks in the last century has prompted to initiate commercial farming of cod in captive conditions. Several approaches have been employed ranging from stock enhancement, capture‐based aquaculture and intensive cod farming. However, except for the enhancement efforts which were carried out for almost a century, efforts on other methods were intermittent coinciding with lower quotas. Intensive farming was attempted in Norway, Scotland, Ireland, Canada, Iceland and Faroe Islands in the 2000s. But it was carried out hastily to cash in the demand for cod in the market even though there were many biological knowledge gaps that are required for a successful aquaculture venture. The reasons for the failure of commercial farming in Norway during the 2000s were not only because of limited knowledge of the biology of cod but also the economic meltdown in Europe in 2008. Cod farming came to a halt; however, the Norwegian National Cod Breeding Program (NCBP) initiated in 2003 continued to operate and produced a fifth generation of a domesticated cod in 2019. Efforts to fill the gaps and the selective breeding for better growth and disease resistance within NCBP have improved the quality of the juveniles produced. We will discuss the past efforts and reasons for failure in farming of cod, how the current situation looks and the future direction in terms of cod biology, political atmosphere and market.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".