Screening method for petroleum-derived aromatic hydrocarbons in wine
Bibliographic record
Abstract
A novel screening method was developed using gas chromatography-mass spectrometry (GC-MS) combined with headspace-solid phase microextraction (SPME) for the detection of various aromatic hydrocarbons in wine. Petroleum-derived products such as toluene, styrene, alkylbenzenes and alkylnaphthalenes were targeted for screening. They were detected by monitoring their characteristic ions (selected ion monitoring) and subsequently quantified using selected deuterium-labelled internal standards. The individual compounds were detected at levels as low as 1 μg/L in red or white wine. The method developed was rapid, simple, solvent-free and sensitive. Application of the method to a tainted red wine confirmed the presence and allowed determination of the level of taint hydrocarbons and agreed with the sensory evaluation (kerosene-like).
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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 | 0.001 | 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) | 0.000 | 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 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".