Classical controlled rolling of low C steels microalloyed with Ti and Mo
Bibliographic record
Abstract
Abstract Two low-C steels, one microalloyed with Ti and the other with Ti and Mo were subjected to a classical controlled rolling schedule using torsion testing. The specific torsion schedules were a simulation of an industrial schedule adapted to the characteristic transformation temperatures of each steel. It is shown that such steels can develop a pancaked austenite, despite the fact that the alloys do not contain Nb. However, compared to Nb bearing steels, restoration between deformation passes is relatively rapid in the pancaking region. In order to reduce the loss of pancaking, the temperatures of the finishing rolling schedule were shifted to lower temperatures. This appeared to greatly reduce the restoration rates, but the transformation in the two phase region occurred towards the end of the final deformation pass. When comparing the two steels, it could be detected that Mo increases the temperature range for pancaking and reduces the restoration rates between deformation passes in the pancaking region.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".