Cooling Curves of Concentrated Alloys, Steelmaking Slag, and Lithium Iron Phosphate
Bibliographic record
Abstract
Abstract Over the past few years, a variety of melting casting projects have been performed, in collaboration with industries and universities. Concentrated alloys and nonmetallic compounds were studied including high-Si cast iron, high-Mn steel, Al-added stainless steel, high-entropy alloy, Permalloy 80 Ni alloy, Stellite Co alloy, steelmaking slag, and lithium iron phosphate (LFP). A melt synthesis of LFP was developed. Cooling curves were measured using the thermal analysis cup method and differential thermal analysis. In addition, the phase diagrams of alloys were calculated using Thermo-Calc. This paper draws on some examples of the measured cooling curves to illustrate the thermal behaviors of melts, along with a quick review of each project.
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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 | 0.000 | 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 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".