Effect of CaO/MgO Ratio on the Product Quality during Tin Smelting
Bibliographic record
Abstract
The existing tin smelting processes have the disadvantages of high smelting temperature, long smelting time and especially high tin losses.In this paper, the effect of basicity on the product quality during tin smelting was studied by monitoring the CaO/MgO ratio.It was found that the iron content in the metal product depends on the Fe/Sn ratio in the slag.A high tin metal product (98.52%Sn and 1.02% Fe) was obtained and a small loss of Sn went into the slag (<10%) at a reduction temperature of 1400 0 C and basicity of 1.2.The low Fe content in the Sn metal would make the subsequent tin refining easier.The Nb and Ta content in the slag increased to 4.96 and 5.06% respectively.The main phases in the slag were Ferrocolumbite, Niobium oxide and Tantalum oxide.The recovery was high for Sn in the metal and Nb/Ta in the slag.
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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 | 0.001 |
| 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) | 0.001 | 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".