Quantitative determination of polar and ionic compounds in petroleum fractions by atmospheric pressure chemical ionization and electrospray ionization mass spectrometry
Bibliographic record
Abstract
The capabilities of atmospheric pressure chemical ionization (APCI) and electrospray ionization (ESI) methods for quantitative analysis of polar and ionic compounds in petroleum fractions have been examined. The requirements of the analysis for sensitivity, linear dynamic range, and structural characterization have been discussed. ESI was found to be approximately two orders of magnitude more sensitive than APCI and is most suitable for the detection of analytes in weak concentrations. Equivalent relative linear dynamic ranges were observed by the two methods (at least three orders of magnitude). For the relatively high analyte concentrations examined here (e.g., 1-100 ppm or higher), the absolute area counts increased linearly with the analyte amount only in APCI, making this method more attractive for quantitative liquid chromatography/mass spectrometry (LC/MS) applications. Nevertheless, a wider range of ionic compounds can be detected by ESI than by APCI.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".