Advances in mass spectrometry for molecular characterization of oil sands naphthenic acids and process chemicals in wetlands
Bibliographic record
Abstract
Advances in mass spectrometry in the authors’ and key collaborators’ research are reviewed for analysis of oil sands naphthenic acids fraction compounds (NAFCs) and industrial process chemicals, sulfolane and alkanolamines, in wetlands. Focus is given to developments of analyses of NAFCs in constructed wetland treatment systems and natural wetlands in the Athabasca oil sands region, Alberta, Canada. The analytical developments are applied to show the utility of wetlands to sequester and oxidize oil sands naphthenic acids. The advancements in molecular characterization led to the first application of high-resolution mass spectrometry (Fourier transform ion-cyclotron resonance and Orbitrap mass spectrometry) for elucidation of toxic mono- and di-carboxylic NAFCs in oil sands environmental samples. Key findings reveal that oil sands NAFCs are not limited to saturated structures but contain a diverse range of components, many of which contain S, N, heteroatomic species and aromatic species. Other developments of mass spectrometry methods for industrial process chemicals show for the first time that the completely water-miscible chemical, sulfolane, translocate to upper portions of cattails at natural wetland sites in the Canadian environment. Likewise, wetland-plant mediated changes of complex mixtures of alkanolamines were revealed based on the coupling of ion chromatography mass spectrometry and ultrahigh resolution mass spectrometry. The advances in mass spectrometry are of particular benefit to Canada, for development of soil and water quality guidelines for oil sands NAFCs and process chemicals. In turn, the water quality guidelines serve to protect Canadian aquatic environments.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".