Improvements in the estimates of ice thickness and production in the Chukchi Sea polynyas derived from AMSR‐E
Bibliographic record
Abstract
For January–March 2003, we use 12.5‐km resolution Advanced Microwave Scanning Radiometer (AMSR) data for the first time in a comparison with Synthetic Aperture Radar (SAR) and Special Sensor Microwave/Imager (SSM/I) data to study two Chukchi coast polynyas, one consisting of many, the other of only a few 25‐km SSM/I pixels. Within these polynyas, the ice thicknesses are derived separately from the SMM/I 37‐GHz and AMSR 36‐GHz channels; the heat fluxes are derived by combining thicknesses with meteorological data. Comparison with ScanSAR data shows that for the large polynya, because AMSR provides better resolution of the surrounding coastline and first‐year ice, the AMSR heat losses are greater than the SSM/I; for the small polynya, AMSR measures its variability even when its area is order of a single SSM/I pixel. This means that AMSR permits more accurate calculation of polynya heat losses, yielding the potential of improved estimates of Arctic polynya 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".