A laboratory study of frazil evolution in a counter-rotating flume
Bibliographic record
Abstract
A series of experiments was carried out using a counter-rotating flume that is housed in a computer-controlled cold room. A digital image process system (DIPS) was used to observe frazil ice processes. In particular, the effects of air temperature and flow velocity on the supercooling and frazil ice processes were examined. The super cooling process was found to be strongly related to air temperature and water depth, but only weakly related to water velocity. The water velocity has a strong influence on frazil evolution, frazil size, and number of the particles, however. The measured frazil size distribution by volume was found to be reasonably well approximated by a log-normal distribution. Frazil growth continues in number and size during supercooling and appears to reach a stable state at the end of the principal period of supercooling. All characteristic parameters of the supercooling processes and frazil size distribution were found to be related to the Reynolds number, an index of the intensity of flow turbulence. This information can be used in the development of models of frazil ice dynamics.Key words: supercooling, frazil ice, distribution, flow velocity, air temperature, turbulence.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".