Determination of Ortho‐ and Retronasal Detection Thresholds for 2‐Isopropyl‐3‐Methoxypyrazine in Wine
Bibliographic record
Abstract
2-Isopropyl-3-methoxypyrazine (IPMP) is a grape-derived component of wine flavor in some wine varieties as well as the causal compound of the off-flavor known as ladybug taint (LBT), which occurs when Harmonia axyridis beetles are incorporated with the grapes during juice and wine processing. The main objective of this study was to obtain robust estimates of the orthonasal (ON) and retronasal (RN) detection thresholds (DTs) for IPMP in wines of differing styles. The ASTM E679 ascending forced choice method of limits was used to determine DTs for 47 individuals in 3 different wines--Chardonnay, Gewürztraminer, and a red wine blend of Baco Noir and Marechel Foch. The group best estimate thresholds (BETs) obtained for IPMP (ng/L) were Chardonnay, ON: 0.32; Gewürztraminer, ON: 1.56, RN: 1.15, and red wine blend, ON: 1.03, RN: 2.29. A large variation in individual DTs was observed. Familiarity with LBT was inversely correlated with DTs for Gewürztraminer, and no difference in thresholds was observed between winemakers and nonwinemakers. We conclude that the human DT for IPMP is extremely low and influenced significantly by wine style and evaluation mode. We recommend against the reporting of single-threshold values for wine flavor compounds, and encourage the determination of consumer rejection thresholds for IPMP in wine.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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 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".