RADARSAT-1 Antarctic Mapping Project: change-detection and surface velocity campaign
Bibliographic record
Abstract
Abstract The RADARSAT-1 Antarctic Mapping Project (RAMP) is a collaboration between NASA and the Canadian Space Agency to map Antarctica using synthetic aperture radar (SAR). The first Antarctic Mapping Mission (AMM-1) was successfully completed in October 1997. Data from the acquisition phase of the 1997 campaign have been used to achieve the primary goal of producing the first high-resolution SAR image map of Antarctica. The Modified Antarctic Mapping Mission (MAMM) occurred during the fall of 2000. The acquisition strategy concentrated on collecting highest- resolution RADARSAT-1 data of Antarctica’s fast glaciers for change detection and feature-retracking estimates of surface velocity. Additionally, extensive data were acquired for interferometric analysis over the entire viewable region, which extends north of 80.1˚ S latitude. This paper summarizes the goals and strategy behind MAMM. It goes on to discuss ice-sheet margin changes observed on several ice shelves around the continent. Margin changes are documented by comparing AMM-1 and MAMM data with earlier datasets including European Remote-sensing Satellite-1 SAR imagery, Landsat imagery, the Antarctic Digital Database (version 1) coastline and Declassified Intelligence Satellite Photography. Analysis reveals a complex pattern of ice-margin advance and retreat without indicating any systematic behavior in ice-sheet extent about the ice-sheet perimeter.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 0.001 |
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".