Macrosegregation of Alloying Elements in Hot Top of Large Size High Strength Steel Ingot
Bibliographic record
Abstract
The chemical heterogeneities of alloying elements were evaluated in the hot top plus the top of a 40-ton ingot of as-cast high strength low alloy steel. The chemical compositions of small samples, taken from a slice cut along the longitudinal axis of the ingot, were obtained using mass spectroscopy. The chemical results were used to construct the chemical heterogeneity maps of C, Mn, Ni, Cr and Mo in the entire slice. The analyses of the different maps indicate the existence of positive segregation for all segregated elements except Ni where no segregation was observed. The most important macrosegregation was revealed in the centerline of the ingot. Carbon presents the highest degree of segregation whereas Mo presents the lowest one. In term of homogeneity degrees, Mn, Ni, Cr and Mo present better homogeneity than C whether in the top of the ingot or in the hot top.
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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 | 0.000 | 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 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".