Characterization of Cigar Tobaccos by Gas Chromatographic/Mass Spectrometric Analysis of Nonvolatile Organic Acids: Application to the Authentication of Cuban Cigars
Bibliographic record
Abstract
A reliable method based on gas chromatographic/mass spectrometric (GC/MS) profiling of nonvolatile organic acids is described for the characterization of cigars. The method involves an aqueous extraction of ground tobacco and selective isolation of the acids by simply stirring strong anion exchange (SAX) disks in the aqueous tobacco extract. The acids are then directly silylated on the disk with N-methyl-N-trimethylsilyl-trifluroacetamide (MSTFA) in acetonitrile in an autosampler vial. Elution of the derivatized acids in situ allows the sample to be directly analyzed by GC/MS without further sample handling. Compared to the conventional disk-extraction technique using a vacuum manifold, this method is much less labor intensive, and is desirable for multiple sample analysis. Nicotinic acid, succinic acid, glyceric acid, malic acid, pyroglutamic acid, threonic acid, citric acid, uracil, and an unidentified acid were reproducibly quantified in tobacco samples. Principal component analysis (PCA) of the acid profiles of the filler tobaccos of 18 Cuban cigars and 31 non-Cuban cigars shows separation of the two groups, indicating that the acid profiles are potentially useful in the authentication of Cuban cigars.
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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 | 0.000 |
| 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".