RADARSAT SAR Sea Ice Deformation. Version 1.0
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Canadian RADARSAT satellite collected 195 synthetic aperture radar (SAR) images of the SHEBA site between November 1, 1997, and October 8, 1998 (roughly one image every 3-5 days). The C-band (5.3 GHz) RADARSAT SAR imaged a swath on the earth 460 km wide (in ScanSAR mode) with a pixel size of 50 m, unhampered by clouds or darkness. The satellite data were received and processed into imagery at the Alaska SAR Facility (ASF) in Fairbanks. Sequential pairs of images were then processed by the RADARSAT Geophysical Processor System (RGPS) at the Jet Propulsion Laboratory (JPL) in Pasadena to derive the motion of the sea ice on a 5-km grid by tracking common features in each pair of images. Thus we have a year-long record of the spatial pattern of ice motion and the radar backscatter in the vicinity of the SHEBA site. Ice deformation (divergence, shear) and ice vorticity are computed from the RGPS ice motion products. This dataset contains 4 sea-ice deformation products containing divergence, shear, and vorticity values based on 4 square regions centered on the SHEBA station: 50 x 50 km, 100 x 100 km, 150 x 150 km, and 200 x 200 km. Additionally, there are 4 graphical products, one of each: divergence, shear, vorticity, and area.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.148 | 0.033 |
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 it