On the relationship between spatial patterns of sea‐ice type and the mechanisms which create and maintain the North Water (NOW) polynya
Bibliographic record
Abstract
Polynyas represent polar oceanic areas with anomalous low sea‐ice concentrations. The North Water (NOW) Polynya refers to a region at the northern end of Baffin Bay which encompasses three separate polynyas. This paper examines the spatial patterns of sea‐ice cover within the NOW region during the winter, spring and fall of 1998 in the context of polynya formation and maintenance mechanisms. To accomplish this a sea‐ice classification scheme for RADARSAT‐1 ScanSAR imagery, obtained between 21 January and 7 December 1998, was developed and implemented within a Geographic Information System (GIS). The results identify a clear and consistent spatial structure of sea‐ice cover throughout the winter, spring and fall of 1998. Temporally, the polynya opened southward along the Canadian coast and westward away from the Greenland coast. Comparison with parallel oceanographic, atmospheric and ice motion studies suggested that the polynya was primarily controlled by a latent heat mechanism with the exception of the west Greenland coast between Whale Sound and Cape York. The underlying mechanism used to explain the polynya's occurrence along this location is delayed ice formation during freeze‐up and a resultant thinner winter ice cover causing earlier spring ablation than surrounding areas. Arguments for oceanic and/or atmospheric sensible heat contributions are made.
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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 | 0.001 |
| 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".