Atlantic cod aquaculture: Boom, bust, and rebirth?
Bibliographic record
Abstract
Abstract The commercialization of a new species through aquaculture is much more complex than the mastery of the production process, or closing the loop, as it is sometimes referred to. Commercial aquaculture is a layer within the global seafood industry, much as wild capture is; however, it places human control at a much earlier phase in the life cycle of the harvested product. As an important species on both sides of the Atlantic, the commercialization efforts for the culture of Atlantic cod are described for four locations, Norway, United Kingdom, New England, and Atlantic Canada that highlight many similar technical challenges and the progress made from the late 1980s through 2012. We also describe some of the marketing challenges faced and how they differ. Technically, the species has been commercialized. Hatcheries and farms in all four countries were successfully established. However, there are clear differences in access to capital for research and industrial expansion from both the private and public sector, social acceptance of farmed fish, as well as the impacts on sales when marketing farmed cod in the context of a global seafood supply. Lower cost species substitution, from either the farmed or wild catch, is also a factor that can have a significant impact on long‐term successful commercialization.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.019 | 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".