Benchmarking growth of farmed Atlantic cod, Gadus morhua: a case study in Ireland
Bibliographic record
Abstract
The growth performance of different stocks of farmed North Atlantic cod over several years in Irish rearing conditions is described. The growth trajectories for all stocks reared were similar. From all growth data, it was found that weight at 180 and 365 days post hatch (dph), with mean values of 17.7 and 158.7 g, respectively, are accessible and useful indicators of hatchery growth performance. The importance of using standard benchmarking points to facilitate concerted and improved research efforts is highlighted here. Growth performance was evaluated against existing predictive models and these were found to be quite robust and very useful within certain constraints. Comparative growth modelling using prevailing ambient sea surface temperature regimes for five different countries (Ireland, Norway, Canada, Iceland and the Faeroes) was also undertaken. Harvest size of 2.5 kg was estimated to be reached in approximately 36 months post hatch in the Faeroes, 38 months in Ireland, 37 months in Norway, 40 months for Canada and up to 42 months in Iceland.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".