Oxidation of Oil Sands Process-Affected Water by Potassium Ferrate(VI)
Bibliographic record
Abstract
This paper investigates the oxidation of oil sands process-affected water (OSPW) by potassium ferrate(VI). Due to the selectivity of ferrate(VI) oxidation, two-ring and three-ring fluorescing aromatics were preferentially removed at doses <100 mg/L Fe(VI), and one-ring aromatics were removed only at doses ≥100 mg/L Fe(VI). Ferrate(VI) oxidation achieved 64.0% and 78.4% removal of naphthenic acids (NAs) at the dose of 200 mg/L and 400 mg/L Fe(VI) respectively, and NAs with high carbon number and ring number were removed preferentially. (1)H nuclear magnetic resonance ((1)H NMR) spectra indicated that the oxidation of fluorescing aromatics resulted in the opening of some aromatic rings. Electron paramagnetic resonance (EPR) analysis detected signals of organic radical intermediates, indicating that one-electron transfer is one of the probable mechanisms in the oxidation of NAs. The inhibition effect of OSPW on Vibrio fischeri and the toxicity effect on goldfish primary kidney macrophages (PKMs) were both reduced after ferrate(VI) oxidation. The fluorescing aromatics in OSPW were proposed to be an important contributor to this acute toxicity. Degradation of model compounds with ferrate(VI) was also investigated and the results confirmed our findings in OSPW study.
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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) | 0.000 | 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".