Removal and biodegradation of naphthenic acids by biochar and attached environmental biofilms in the presence of co-contaminating metals
Bibliographic record
Abstract
This study evaluated the efficacy of using a combined biofilm-biochar approach to remove organic (naphthenic acids (NAs)) and inorganic (metals) contaminants from process water (OSPW) generated by Canada's oil sands mining operations. A microbial community sourced from an OSPW sample was cultured as biofilms on several carbonaceous materials. Two biochar samples, from softwood bark (SB) and Aspen wood (N3), facilitated the most microbial growth (measured by protein assays) and were used for NA removal studies performed with and without biofilms, and in the presence and absence of contaminating metals. Similar NA removal was seen in 6-day sterile N3 and SB assays (>30%), while biodegradation by SB-associated biofilms increased NA removal to 87% in the presence of metals. Metal sorption was also observed, with up to four times more immobilization of Fe, Al, and As on biofilm-associated biochar. These results suggest this combined approach may be a promising treatment for OSPW.
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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) | 0.001 | 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 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".