A NEW SET OF CERTIFIED REFERENCE MATERIALS OF THE CHEMICAL COMPOSITION OF THE IRON ORES
Bibliographic record
Abstract
The study assumed the production of ten certified reference materials of the chemical composition of raw ores, magnetite and hematite concentrates and pellets.The raw materials were obtained from Ukraine, Russia, Liberia, Brazil, Canada, and Norway.Their chemical composition was confirmed by the WD XRF method, and the mineral composition was analyzed with the use of X-ray diffraction.Radioactivity studies were also carried out.Dried, ground and mixed materials were subjected to homogeneity tests, which were carried out on samples melted in a mixture of lithium borates, using a ZSX Primus 2 X-ray spectrometer.Based on the results of the homogeneity test and the use of analysis of variance (ANOVA) for the results of individual determinations, the contribution of homogeneity in the uncertainty of the certified value was calculated.International certification round-robin program of tests with fourteen laboratories was organized and carried out.The results of the analyses were developed statistically in accordance with ISO Guide 35:2017.Certificates, data sheets and labels were developed.The production was carried out in accordance with the requirements of PN-EN ISO 17034.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".