Advances in mass spectrometric characterization of naphthenic acids fraction compounds in oil sands environmental samples and crude oil—A review
Bibliographic record
Abstract
There has been a recent surge in the development of mass spectrometric methods for detailed characterization of naphthenic acid fraction compounds (all C(c)H(h)N(n)O(o)S(s), species, including heteroatomic and aromatic components in the acid-extractable fraction) in environmental samples. This surge is driven by the increased activity in oil sands environmental monitoring programs in Canada, the exponential increase in research studies on the isolation and toxicity identification of components in oil sands process water (OSPW), and the analytical requirements for development of technologies for treatment of OSPW. There has been additional impetus due to the parallel studies to control corrosion from naphthenic acids during the mining and refining of heavy bitumen and crude oils. As a result, a range of new mass spectrometry tools have been introduced since our last major review of this topic in 2009. Of particular significance are the developments of combined mass spectrometric methods that incorporate technologies such as gas chromatography, liquid chromatography, and ion mobility. There has been additional progress with respect to improved visualization methods for petroleomics and oil sands environmental forensics. For comprehensive coverage and more reliable characterization of samples, an approach based on multiple-methods that employ two or more ionization modes is recommended. On-line or off-line fractionation of isolated extracts, with or without derivatization, might also be used prior to mass spectrometric analyses. Individual ionization methods have their associated strengths and weaknesses, including biases, and thus dependence upon a single ionization method is potentially misleading. There is also a growing trend to not rely solely on low-resolution mass spectrometric methods (<20,000 resolving power at m/z 200) for characterization of complex samples. Future research is anticipated to focus upon (i) structural elucidation of components to determine the correlation with toxicity or corrosion, (ii) verification of characterization studies based on authentic reference standards and reference materials, and (iii) integrated approaches based on multiple-methods and ionization methods for more-reliable oil sands environmental forensics.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".