Using SWOT for ocean monitoring and prediction off Canada’s west and east coasts
Bibliographic record
Abstract
Surface Water and Ocean Topography (SWOT) sea surface height anomaly (SSHA) data were used for ocean monitoring and prediction off Canada’s west and east coasts. For the ocean monitoring, a method was developed to reconstruct weekly, monthly and seasonal SSHA fields on a regular spatial grid. Surface geostrophic current anomalies were derived from the reconstructed SSHA fields. Experiments were carried out to refine the reconstruction method and to assess temporal and spatial scales in which SSHA and current features can be reconstructed properly. The mean surface circulation field from a coastal ocean model was added to the SWOT surface current anomalies to produce the absolute currents. For the ocean prediction, after successful Observing System Simulation experiments, real SWOT data were assimilated in the Regional Ice Ocean Prediction System demonstrating significant improvements in SSHA statistics. Further efforts to investigate how to constrain small-scale features from SWOT are being pursued in a 1/36th degree resolution configuration for the Northwest Atlantic Ocean.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".