Two Challenges to the System of Periclase Quality Evaluation
Bibliographic record
Abstract
A new method of estimating the fused periclase quality – the revision of international standards. Quality and service life of refractories on the basis of fused periclase depend to a large extent upon the size of periclase crystals and its mineralogical composition. During fusion of periclase it is impossible to obtain completely homogeneous material with identical crystals size. That is why it is generally accepted to evaluate quality of fused periclase by the average crystals size. Measurements of this item are usually done with the help of generally adopted method of chords, which was developed in the last century and has a number of drawbacks. Magnezit Group developed a new objective method of digital analysis during microscopic examination of structural elements of fused periclase. It allows to considerably improve objectivity of obtained data. The main feature of the new method is application of the system of images analysis, which allows to carry out in automatic mode measurements on the preliminary created digital model of the whole area of the polished section. With the help of the digital model it is possible to calculate average size of fused periclase crystals taking into account number of crystals as well as percentage of the area occupied by them. Does CaO/SiO2 ratio influence service life of refractories? New view of old rules. Till today it was considered that one of the characteristics of fused periclase quality is coefficient of basicity – CaO/SiO2, ratio, which should be more than 2. Magnezit Group carried out investigations of coarse-crystalline fused periclase with MgO >97.5 % content and with various CaO/SiO2 ratios. We present in this report the main study results: if the impurities content is low in the fused periclase with MgO >97.5 %, then coefficient of basicity exerts limited influence onto the service life of periclase-carbon bricks.
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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 | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.006 |
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".