CGU HS Committee on River Ice Processes and the Environment 14th Workshop on the Hydraulics of Ice Covered Rivers
Bibliographic record
Abstract
Based on recent studies, the classification of river ice cover types from RADARSAT-1 SAR images is possible with a relatively high degree of confidence. With satellite radar ice maps, the dominant ice cover types can be identified, ice type boundaries can be observed and ice cover production processes can sometimes be monitored. The ice maps can help locate the head of the complete ice cover and the location of heavily consolidated events, which are features of particular interest for hydropower companies or flood forecasters. However, misclassification of ice cover types often occurs due to the complex and varying characteristics of the ice itself and to the characteristics of the sensor. In order to assess the efficiency of different image classification algorithms, this study investigates a quantitative validation analysis over the Peace River, Alberta and the Saint-François River, Québec. Ground truth was based on georeferenced aerial photos for the Peace River site and on ground photos for the Saint-François River site. Three different
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.038 | 0.010 |
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".