Metal(loid)s Removal Response to the Seasonal Freeze–Thaw Cycle in Semi-passive Pilot Scale Bioreactors
Bibliographic record
Abstract
Abstract There is an increasing demand for cost-effective semi-passive water treatment that can withstand challenging climatic conditions and effectively and sustainably manage mine-impacted water in (sub)arctic regions. This study investigated the ability of four pilot-scale bioreactors inoculated with locally sourced bacteria and affected by a freeze–thaw cycle to remove selenium and antimony. The bioreactors were operated at a Canadian (sub)arctic mine for a year. Two duplicate bioreactors were installed in a heated shed that was maintained at 5 °C over the winter, while two other duplicates were installed outdoors and left to freeze. The removal rate of selenium and antimony was monitored weekly, while a genomic characterization of the microbial populations in the bioreactors was performed monthly. The overall percentage of selenium and antimony removal was similar in the outside (10–93% Se, 20–96% Sb) and inside (35–94% Se, 10–95% Sb) bioreactors, apart from the spring thawing period when removal in the outdoor bioreactors was slightly lower for Se. The dominant taxonomic groups of microbial populations in all bioreactors were Bacteroidota, Firmicutes, Desulfobacterota and Proteobacteria. The microbial population composition was consistent and re-established quickly after spring thaw in the outside bioreactors. This demonstrated that the removal capacity of bioreactors inoculated with locally sourced bacteria was mostly unaffected by a freeze–thaw cycle, highlighting the strength of using local resources to design bioreactors in extreme climatic conditions.
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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 | 0.001 | 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 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".