Authentication of Geographic Origin of Wine by using EDXRF and Multivariate Statistics
Bibliographic record
Abstract
The controlled geographic origin of wine is value added and therefore of great interest to both consumers and manufacturers. It is widely accepted that soil is important component of a wine region terroir, but the reflection of the soil characteristics into the wine, and especially soil elemental composition which is very specific for each vineyard location, is not yet fully understood. By assuming that link between elemental composition of soil and wine exists, the discrimination technique Between Group - Principle Component Analysis (BG-PCA) was used on log(csoil)/log(cwine) ratios of elements Ca, Mn, Fe, Cu, Zn, Rb and Sr to find and evaluate differences between wine regions. The results have been shown for 16 wine samples of Graševina (variety of grapevine Riesling), which can be grouped in 5 viniculture regions of the continental part of the Republic of Croatia. Wine samples pre-concentrated by freeze drying and corresponding soil samples were analyzed by the EDXRF technique.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".