Interpretation of theoretical scattering mechanisms extracted from polarimetric target decomposition algorithms for sea ice applications
Bibliographic record
Abstract
Outputs from coherent and incoherent decomposition methods are compared over a sea ice environment selected so that surface scattering be the dominant mechanism all over the scene. Our field observations revealed two types of ice: one formed at the onset of the winter season and the other formed later at spring in leads. Pressure ridges and rubble fields were also present on the old ice surfaces. Both methods were able to draw a satisfying map of the two ice types and localize pressure ridges. However the application of a Wishart classifier gives an improved resolution over the Pauli RGB. Two main differences emerge from our results. The intensity fluctuations of the return are better revealed on the Pauli RGB with forward scattering showing as dark areas. A parallel consequence is that areas where a strong forward scattering occurred were wrongly classified as dominated by a volume scattering mechanism. The incoherent method successfully classified all surfaces as dominated by a surface scattering mechanism.
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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) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".