A coupled ice‐ocean modeling study of the northwest Atlantic Ocean
Bibliographic record
Abstract
A coupled ice‐ocean modeling system is developed for the northwest Atlantic Ocean based on the second version of the Los Alamos sea ice model and a regional ocean circulation model. The coupled ice‐ocean system differs from other coupled systems for the same region mainly in two ways. First, the semi‐prognostic method suggested by Sheng et al. [2001] is used in the ocean component. This method adjusts the momentum equation of the ocean component to reduce drift of the modeled ocean state, allowing us to carry out a multiyear simulation. Second, the sea ice component uses the elastic‐viscous‐plastic ice rheology developed by Hunke and Dukowicz [1997] and Winton's [2000] three‐layer thermodynamics. The coupled system is forced by climatological monthly mean atmospheric forcing at the atmosphere/ocean, atmosphere/ice interface, and oceanic forcing at the model open boundaries. The system is integrated for 3 years. Model results from the third year compare favorably with the observations in the region. The coupled system reproduces reasonably well the phase and magnitude of the annual cycle of sea ice. We demonstrate the effect of the ice heat capacity, previously unaccounted for in earlier model results of this region, in delaying the springtime sea‐ice melt on the Labrador and Newfoundland Shelves.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".