Assessing the Impact of Smoke Exposure in Grapes: Development and Validation of a HPLC-MS/MS Method for the Quantitative Analysis of Smoke-Derived Phenolic Glycosides in Grapes and Wine
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Bushfires occur frequently in the vicinity of grape growing regions, resulting in smoke drifting over the vineyards. Wine made from smoked grapes is often downgraded or unfit for sale due to negative sensory characters. To manage or avoid the risk of producing smoke-affected wine, a diagnostic assay was developed for assessing the extent of smoke exposure in grapes and the resulting wines. The method relies on the quantitation of the glycosidic grape metabolites that are formed from major volatile phenols present in smoke. Using HPLC-MS/MS with APCI, a quantitation method for phenolic glycosides as smoke marker compounds was developed and validated. The method was confirmed to be of sufficient sensitivity and reliability to use as a diagnostic assay. On the basis of phenolic glycoside concentrations, grapes or wine can be assessed as smoke exposed or not, and the relative intensity of smoke exposure can be determined.
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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) | 0.000 | 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 it