A duplicate column study of arsenic, cadmium and zinc treatment in an anaerobic bioreactor based on a system operated by Teck Cominco in Trail, British Columbia
Bibliographic record
Abstract
The study’s objective was to identify and profile the treatment mechanisms within an anaerobic bioreactor (ABR) designed to remove high concentrations of arsenic, cadmium and zinc from contaminated drainage. The experiment used duplicate 15.6 L ABR columns, containing limestone and an organic substrate. The design and operation parameters were based on a larger field scale system operated by Nature Works Remediation for Teck Cominco in Trail, British Columbia. After an acclimatization period, the experiment was conducted for six months at various hydraulic loadings intended to evaluate optimal and stressed conditions, as well as, the ABR’s ability to re-establish optimal conditions. The study suggested that cadmium and zinc were removed as metal sulphides after 20 hours residence time. The behaviour of arsenic was independent of cadmium and zinc, and the majority was removed within 7 hours residence time. This was attributed to its adsorption to iron. Correlations of arsenic and iron concentrations throughout the organic substrate demonstrated that adsorption was inconsistent and unreliable as a treatment mechanism without the subsequent oxic conditions at the column’s headwater. Considerations for the field were identified for treatment, management of hydraulic loadings, and maintenance of an ABR.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".