A conceptual model of an Arctic sea
Bibliographic record
Abstract
We propose a conceptual model for an Arctic sea that is driven by river runoff, atmospheric fluxes, sea ice melt/growth, and winds. The model domain is divided into two areas, the interior and boundary regions, that are coupled through Ekman and eddy fluxes of buoyancy. The model is applied to Hudson and James Bays (HJB, a large inland basin in northeastern Canada) for the period 1979–2007. Several yearlong records from instruments moored within HJB show that the model results are consistent with the real system. The model notably reproduces the seasonal migration of the halocline, the baroclinic boundary current, spatial variability of freshwater content, and the fall maximum in freshwater export. The simulations clarify the important differences in the freshwater balance of the western and eastern sides of HJB. The significant role played by the boundary current in the freshwater budget of the system, and its sensitivity to the wind‐forcing, are also highlighted by the simulations and new data analyses. We conclude that the model proposed is useful for the interpretation of observed data from Arctic seas and model outputs from more complex coupled/climate models.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".