THE EXPERIENCE ON INVESTIGATION OF CLEANER NONFERROUS METALS PRODUCTION ENTERPRISES IN CANADA
Bibliographic record
Abstract
As a member of China Cleaner Nonferrous Metals Production Investigation Group to Canada, author investigated two techniques for wastewater treatment, CANSOLV low-SO_2 purification and HDS process, for Noranda Zinc Smelter, INCO's Nickel Smelter and Copper Refining Plant in Canada. The experience from the investigation is that cleaner production technology has the characteristics of energy saving, less consumption and low pollution, reflected in the advanced smelting process, equipment and management; the so-called cleaner technology is relative and steadily improved along with social progress; to put the cleaner technology into practice is a cardinal way to eliminate industrial environment pollution in China. For this reason, the advanced cleaner production technologies should be introduced so as to speed up the expansion of cleaner production technology in China.
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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".