State estimation of the Labrador Sea with a coupled ocean/sea-ice adjoint model
Bibliographic record
Abstract
Sea ice (SI) and ocean variability in marginal polar and subpolar seas are closely cou-pled. SI variability in the Labrador Sea is of climatic interest because of its relationship to deep convection/mode water formation, carbon sequestration, and Northern Hemisphere atmospheric patterns. Historically, quantifying the link between the region’s observed SI and oceanic variability has been limited due to in situ observation paucity and technical challenges associated with synthesizing ocean and SI observations with a three-dimensional time-evolving dynamically consistent numerical model. To elaborate upon the relationship between SI and ocean variability, a one year (1996-1997) state estimate of the ocean and sea ice state in Labrador Sea and Baffin Bay is constructed and analyzed. The estimate is a synthesis of a regional coupled 32 km ocean and sea ice model with a suite of contemporary in situ and satellite hydrographic and SI data.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".