Characterization of dicarboxylic naphthenic acid fraction compounds utilizing amide derivatization: Proof of concept
Bibliographic record
Abstract
RATIONALE: The characterization of naphthenic acid fraction compounds (NAFCs) in oil sands process affected water (OSPW) is of interest for both toxicology studies and regulatory reasons. Previous studies utilizing authentic standards have identified dicarboxylic naphthenic acids using two-dimensional gas chromatography hyphenated to time-of-flight mass spectrometry (GC × GC/TOFMS). The selective derivatization of hydroxyl groups has also recently aided in the characterization of oxy-NAFCs, and indirectly the characterization of dicarboxylic NAFCs. However, there has been no previous report of derivatization being used to directly aid in the standard-free characterization of NAFCs with multiple carboxylic acid functional groups. Herein we present proof-of-concept for the characterization of dicarboxylic NAFCs utilizing amide derivatization. METHODS: Carboxylic acid groups in OSPW extract and in a dicarboxylic acidstandard were derivatized to amides using a previously described method. The derivatized extract and derivatized standard were analyzed by direct-injection positive-mode electrospray ionization ((+)ESI) high-resolution mass spectrometry (HRMS), and the underivatized extract was analyzed by (-)ESI MS. Tandem mass spectrometry (MS/MS) was carried out on selected ions of the derivatized standard and derivatized OSPW. Data analysis was carried out using the Python programming language. RESULTS: The distribution of monocarboxylic NAFCs observed in the amide-derivatized OSPW sample by (+)ESI-MS was generally similar to that seen in underivatized OSPW by (-)ESI-MS. The dicarboxylic acid standard shows evidence of being doubly derivatized, although the second derivatization appears to be inefficient. Furthermore, a spectrum of potential diacid NAFCs is presented, identified by both charge state and derivatization mass. Interference due to the presence of multiple derivatization products is noted, but can be eliminated using on-line separation or an isotopically labelled derivatization reagent. CONCLUSIONS: Proof of concept for the characterization of dicarboxylic NAFCs utilizing amide derivatization is demonstrated. Furthermore, (+)ESI-HRMS of the derivatized monocarboxylic NAFCS yields similar information to (-)ESI-MS analysis of underivatized NAFCs, with the benefit of added selectivity for carboxylic acid species and the characterization of diacids.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".