Identification of individual thiophene‐, indane‐, tetralin‐, cyclohexane‐, and adamantane‐type carboxylic acids in composite tailings pore water from Alberta oil sands
Bibliographic record
Abstract
RATIONALE: Naphthenic acids (NAs) accumulate in oil sands process-affected water (OSPW) as a result of the water-based extraction processes, and represent one of the toxic fractions in OSPW. They exist as a complex mixture and so the development of an analytical method to characterize and quantify individual acids has been an on-going challenge. The multidimensional separation technique of two-dimensional gas chromatography (GC × GC) has the potential to provide a fingerprint of the sources of NAs and can potentially resolve individual analytes for target analysis. However, the identity and toxicity of a large proportion of the acids present in tailing waters are still unknown. METHODS: Comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry (GC × GC/TOFMS) was used to characterize NAs in a pore water sample from a Syncrude composite tailings (CT) deposit in Fort McMurray, Alberta, Canada. The extractable organic acid fraction was derivatized with diazomethane and the structures of selected resolved esters were elucidated through interpretation of their electron ionization (EI) mass spectra and, if available, confirmed by comparison with the spectra of reference standards. RESULTS: The high resolving power of the GC × GC/TOFMS technique allowed for the structural elucidation of numerous as yet unidentified acids in the CT pore water sample such as carboxylic acids containing a thiophene, indane, tetralin or cyclohexane moiety. Seventeen members of the previously reported class of adamantane-type carboxylic acids in oil sands process water could also be identified in the sample. CONCLUSIONS: This study underlines the complexity of naphthenic acid isomer distributions in composite tailings and provides a useful inventory of individual acids.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".