The hydrodynamic foundation for salmon lice dispersion modeling along the Norwegian coast
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Norway has complicated dynamics in the coastal ocean and in the fjords. In this area is also the largest salmon aquaculture industry in the world. The salmon industry is valuable for Norwegian economy worth more than 60 billion NOK. Thus, it is important to know the physical oceanography along the coast, even variability on short temporal and spatial scales (h/km), to be able to quantify environmental effects of the aquaculture industry. This is the motivation behind the implementation of a current model covering the whole coast of Norway with a relatively high spatial grid size of 800 m. The NorKyst800 is an implementation of the ROMS current model with an elaborated system of forcing and boundary conditions. This model has an important role for Norwegian authorities in various management purposes. We show that the NorKyst800 results are realistic and typically deviating at most by 1 °C and one unit in salinity from observations. The currents in the upper 10–20 m of the water column vary in a similar way as observed current and the agreement is good. The usefulness of a tool like the NorKyst800 is illustrated by an example of dispersion of salmon lice which is the biggest problem the salmon industry presently is facing. Detailed information, as can be provided by NorKyst800, is needed to fully understand and quantify environmental effects of the aquaculture industry. Similar modeling systems describing the planktonic salmon lice concentration operationally could be beneficial also in other salmon-producing countries like Scotland, Canada, or Chile. The major requirement will be access to updated number of fish and female lice per fish on a weekly time scale.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it