MAGIC: MAp-Guided Ice Classification System
Bibliographic record
Abstract
A MAp-Guided Ice Classification (MAGIC) system is described and demonstrated. MAGIC is designed specifically to read and interpret synthetic aperture radar (SAR) sea ice images using associated ice maps as provided by the Canadian Ice Service (CIS). An ice chart is manually created at the CIS based on the corresponding SAR image and other ancillary data to provide ice concentrations, types, and floe sizes within enclosed "polygon" regions. MAGIC uses such information as input and then generates a sensor resolution (pixel-based) ice map for each polygon, a product not feasibly produced manually. The primary feature of the current MAGIC version 1.0 is its segmentation module, which is evaluated successfully on a number of images. MAGIC is designed to be used not only as a specific tool for sea ice interpretation but also as a general platform for interpreting generic digital imagery using implemented fundamental and advanced algorithms.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".