Study on mercury speciation during the course of baking waste alkaline zinc manganese batteries
Bibliographic record
Abstract
Pollution of mercury in the environment was serious issue and mercury from batteries was attentioned. The work chose waste alkaline zinc manganese batteries and baking experiment was processed in a tubular furnace. According to the analytical method of mercury in coal Combustion (Ontario-Hydro), the experiment studied the speciation and distribution of mercury during baking. The results indicated that the removal ratio of mercury was 100%, and the concentration of total mercury in the end gas was about 186.41 mg·m -3 ~194.86 mg·m -3 .In the gaseous mercury, the content of Hg0 was about 82.88%~86.64% and Hg 2+ was about 6.02%~6.29%,which showed that the majority of gaseous mercury went into end gas by Hg0, So we could reclaim mercury from waste alkaline zinc manganese batteries by condensing end gas directly.
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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 | 0.000 | 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".