Comparison of COSMO-SkyMed and RADARSAT-2 offset tracking results on David-Drygalski glacier (Antarctica) surface velocities
Bibliographic record
Abstract
This note is about the comparison of coregistration offset tracking velocities of a glacier obtained with SAR sensors characterized by different wavelengths and spatial resolutions: Cosmo-SkyMED (X band) and RADARSAT-2 (C band). The study area is represented by the initial part of the David Glacier, in Antarctica, which is the most important outlet glacier of Victoria Land. Particular attention has been devoted to understand the role of polarization and penetration depth of the incident wavelength, which represent key parameters in determining the effective incidence angle and so, for this reason, affecting also derived velocities. Further investigation is needed to complete this analysis, considering also geophysical data and tidal effects. In particular, we focused our attention on the initial portion of the David glacier, comprising the grounding line (which is the line where the glacier begins to be floating on the sea surface), represented in fig. 3 [1]. The processed dataset consists of four COSMO-SkyMed (in the following simply CSK) Stripmap scenes and two RADARSAT-2 scenes in quad polarization Wide Fine Beam mode, made available respectively by Italian and Canadian Spatial Agencies through the “COSMO-SkyMed/RADARSAT-2 Initiative Joint Announcement of Opportunity” (Proposal id 2873/5247).
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.
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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".