The Characterization of Basic Petroleum Extracts by High-Resolution Mass Spectrometry and Simultaneous Orthogonal Acceleration Time-of-Flight−Magnet Scanning Tandem Mass Spectrometry
Bibliographic record
Abstract
A hybrid double-focusing high-resolution magnetic sector−orthogonal acceleration time-of-flight (oa-TOF) tandem mass spectrometer has been used for the characterization of the basic compounds in a whole crude oil and its 400−414 °C distillation cut. Detailed compositional characterization is obtained from high-resolution experiments. Structural information is obtained from automated magnet scanning mass spectroscopy (MS/MS) experiments that are conducted by continuous oa-TOF data acquisition and simultaneous scanning of the magnet. Solid-phase weak cation exchange is used to remove the basic compounds from the hydrocarbon matrix. Samples are introduced into the mass spectrometer via a dynamic batch inlet system. Molecular ions are produced by charge exchange chemical ionization. The most-abundant compounds in the two basic extracts are due to the C n H 2 n + z N and C n H 2 n + z NS compound classes. Other compound classes of lower concentration are also detected (−NO, −SON, −NO 2, −O, −SO, −O 2, −SO 2 ). The contour plot of the MS/MS data for the 400−414 °C extract has revealed two characteristic peak patterns: (i) a series of peaks parallel to the precursor ion series, containing information about the degree of alkyl substitution, and (ii) a series of peaks parallel to the MS-1 axis containing information about the aromatic nuclei. Despite the complexity of the data, a substantial structural similarity between the various basic nitrogen compounds is indicated by the two peak patterns. The important capability of the simultaneous MS/MS method to provide structural information about isobaric peak components is demonstrated. The chemical formulas of selected isobaric precursor ions are validated, and structures consistent with their product ion spectra are proposed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".