Système de traitement automatisé du gouvernement canadien pour la détection des variations et l'analyse des déformations du sol à partir des données de radar à synthèse d'ouverture de RADARSAT-2 et de la mission de la Constellation RADARSAT :description et guide de l'utilisateur
Bibliographic record
Abstract
Remote sensing using Synthetic Aperture Radar (SAR) offers powerful methods for monitoring ground deformation from both natural and anthropogenic sources. Advanced analysis techniques such as Differential Interferometric Synthetic Aperture Radar (DInSAR), change detection, and Speckle Offset Tracking (SPO) provide sensitive measures of ground movement. With both the RADARSAT-2 and RADARSAT Constellation Mission (RCM) SAR satellites, Canada has access to a significant catalogue of SAR data. To make use of this data, the Canada Centre for Mapping and Earth Observation (CCMEO) has developed an automated system for generating standard and advanced deformation products from SAR data using both DInSAR and SPO methods. This document provides a user guide for this automated processing system.
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How this classification was reachedexpand
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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 teacher head, 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".