Advanced Analytical Mass Spectrometric Techniques and Bioassays to Characterize Untreated and Ozonated Oil Sands Process-Affected Water
Bibliographic record
Abstract
Oil sands process-affected water (OSPW) is a toxic and poorly biodegradable mixture of sand, silt, heavy metals, and organics. In this study, qualitative and quantitative comparisons of naphthenic acids (NAs) were done using ultraperformance liquid chromatography time-of-flight mass spectrometry (UPLC TOF-MS), Fourier transform ion cyclotron resonance (FT-ICR) MS, and ion mobility spectrometry (IMS). The unique combination of these analyses allowed for the determination and correlation of NAs, oxidized NAs, and heteroatom (sulfur or nitrogen) NAs. Despite its lower resolution, UPLC-TOF MS was shown to offer a comparable level of reliability and precision as the high resolution FT-ICR MS. Additionally, the impacts of ozonation (35 mg/L utilized ozone dose) and subsequent NAs degradation on OSPW toxicity were assessed via a collection of organisms and toxicity end points using Vibrio fischeri (nonspecific), specific fish macrophage antimicrobial responses, and fish olfactory responses. Fish macrophages exposed to ozonated OSPW for 1 week showed higher production of reactive oxygen and nitrogen intermediates; however, after 12 weeks the responses were reduced significantly. Fish olfactory tests suggested that OSPW interfered with their perception of odorants. Current results indicate that the quantification of NAs species, using novel analytical methods, can be combined with various toxicity methods to assess the efficiency of OSPW treatment processes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".