<b>River Ice Engineering / Ingénierie des glaces fluviales</b>A digital image processing system to characterize frazil ice
Bibliographic record
Abstract
The detection, measurement, and characterization of frazil ice particles is a necessary first step in advancing our understanding of frazil ice processes as well as improving models. The detection of frazil ice has been accomplished in a number of ways. Herein, a digital image processing system to characterize frazil in a laboratory environment is described. The system is part of an ice research facility that uses a counter-rotating flume to generate frazil ice. Frazil ice is detected using a cross-polarized light technique. The system acquires digital gray-scale images of frazil ice that are analyzed and manipulated digitally to elucidate the temporal and spatial variation of frazil ice characteristics. For example, the system can be readily used to determine the size distribution of frazil ice particles, the vertical distribution of frazil, or the concentration of frazil ice.Key words: frazil ice characterization, progressive scan camera, frame grabber, digital image, gray scale, processing system, pixel, binary image.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.018 | 0.007 |
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".