On the link between SAR‐derived sea ice melt and development of the summer upper ocean mixed layer in the North Open Water Polynya
Bibliographic record
Abstract
We examine the ability of SAR‐derived landfast sea ice thermodynamic state surrounding the North Water Polynya to predict the timing of a shallow, stably stratified summer ocean mixed layer in the region. Radarsat‐1 ScanSAR is used to derive melt and pond onset dates over landfast sea ice surrounding the polynya, describing its thermodynamic evolution. Salinity and temperature profiles, connected in time and space, are complemented by potential density profiles and mixed layer depths, which describe the evolution of the upper ocean mixed layer between 4 April and 21 July 1998. Surface salinity driven potential density stratification and summer mixed layer depths are temporally coincident. Sea ice–ocean connection is first described at the local scale, then regionally. At the local scale, a reduction in surface salinity occurs between the melt and pond onsets over landfast sea ice. At the polynya scale, interpolated pond onset date is highly effective at predicting the timing of a thin, stably stratified summer ocean mixed layer; this has consequences for the potential prediction of timing of maximum ecosystem productivity.
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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 | 0.002 |
| 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 | 0.000 | 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".