Analysis of the current state of molybdenum mineral and raw material base, mining and processing of molybdenum-containing ores
Bibliographic record
Abstract
Molybdenum has a complex of practically significant properties and is widely used for alloying steels and cast irons, in the composition of alloys of various purposes, as well as a structural material in pure form. Molybdenum belongs to the group of rare metals, which causes the relevance of analytical research of the modern state of the mineral- raw material base of molybdenum, extraction and processing of molybdenum-containing ores. The results of analysis of the mineral-raw material base of molybdenum of foreign countries and Russia, assessment of prospects of its expansion are presented. The confirmed world molybdenum resources amount to 12 million tons, including domestic – 2 million tons. 75% of molybdenum reserves are concentrated in the USA, China, Chile, Peru and Canada. Description of the types of deposits of molybdenum, copper-molybdenum and molybdenum-tungsten ores, the main types of molybdenum minerals has been quoted. Methods of ore concentration of various composition for production of molybdenum concentrates, additional enrichment of molybdenum concentrate and industrial practice of molybdenum concentrate processing are considered. In terms of ore quality domestic and foreign raw material base of molybdenum are comparable. 63% of domestic production of molybdenum-containing ores is provided by OJSC “Sorsky GOK”, 33% – OJSC “Zhirekenskiy GOK”. These enterprises produce molybdenum concentrates of grades КМФ-5, КМФ-6, КМФ-7. Their production capacity is about 12 thousand tons of concentrate per year. Molybdenum concentrates are processed by pyro- and hydrometallurgical methods and are an industrial product for production of ferromolybdenum and its chemical compounds. The total capacity of molybdenum concentrate processing plants is 300 thousand tons per year.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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".