Characterization of Naphthenic Acids by Gas Chromatography-Fourier Transform Ion Cyclotron Resonance Mass Spectrometry
Bibliographic record
Abstract
During the bitumen extraction from the oil sands of Alberta, large volumes of process water containing naphthenic acids are stored in tailing ponds. The naphthenic acids along with other components in the processed waters are known to be toxic in aquatic environments. In view of the complex matrix and the toxicity of the processed waters, there is a need for complementary analytical techniques for comprehensive characterization of the naphthenic acid mixtures. This study reports the online gas chromatographic separation of naphthenic acid mixtures prior to ultrahigh resolution mass spectrometry detection, using electron and chemical ionization. Two oil sands processed water samples and two groundwater samples were characterized to evaluate the performance of the instrumental technique. The high mass resolution of the system enabled visualization of the data using Kendrick mass defect plots. The addition of gas chromatographic separations enabled visualization of the data as unique compound class elution fingerprints. The technique is demonstrated to be a valuable tool for chemical fingerprinting of naphthenic acids.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.001 | 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 teacher head, 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".