Effect of Stirring on Crystal Morphologies and on Macro-Segregation
Bibliographic record
Abstract
To minimize the macro-segregation in continuously cast steel slabs, the effects of the stirring on the macro-segregation were studied. Industrial findings by the metallographic observations of the steel slabs showed macro-segregation was improved by the refinements of crystals. It was also found that the stirring at low fraction solid refined crystals. The unsolidified liquid core of the continuously cast slab with the optimum stirring was well packed with the refined crystals whereas it was not with coarse equiaxed crystals. The analogue study with experiments of Pb-Sn alloy showed, similarly as with steel slabs, the stirring at low solid fraction refined crystals. Also, the artificially created cavity in a mush was well packed with the refined, globular, crystals whereas it was not with the coarse dendritic crystals. Thus, it is considered the stirring at the low solid fraction is advantageous to refine crystals and to improve macro-segregation.
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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 | 0.005 | 0.001 |
| 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 | 0.001 |
| 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".