A case-study in tracking 1998 polynya ice dynamics in Smith Sound, North Water polynya region, Canadian Arctic, using RADARSAT-1 data
Bibliographic record
Abstract
Abstract Monitoring ice motion provides insight into the relative contributions of atmospheric and oceanic forcing to polynya dynamics In this study ice kinematics in the North Water (NOW) region, northern Baffin Bay Canadian Arctic are determined using time-sequential RADARSAT-1 ScanSARWide imagery (from the period January-December 1998), processed by the automated ice-tracking algorithm (Tracker) currently used at the Canadian Ice Service (CIS). A case-study is then carried out on the Smith Sound region from January till the end of june 1998 to monitor polynya formation, maintenance and disintegration. This has two objectives: (1) to evaluate satellite ice-motion products as a means of better understanding the relative contributions of latent- and sensible-heat mechanisms responsible for the formation and behaviour of the NOW polynya, and (2) to study the influence of winds on regional sea-ice motion. Derived ice-motion maps were validated using in situ ice beacons deployed onto floes in the NOW region during the 1998 ship-based science experiment. Tracker-derived displacement and directional regressions were 0.93 and 0.79, respectively, with a total standard error of 3.6 km in magnitude and 38.8° in direction. Analysis of monthly mean ice-motion maps shows that a significant export of ice occurs from the polynya. A comparison of weekly-averaged ice motion with the mean wind-field data suggests that ice export in Smith Sound is influenced by synoptic-scale atmospheric pressure systems.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".