A New Validated Method for Rapid Determination of OLEU Concentration in Dietary Supplements: Comparison with Total Phenol Content and Antioxidant Activity
Bibliographic record
Abstract
The market for olive leaf dietary supplements is expanding rapidly and is valued at $437.15 million today. However, information on the control of these products is sketchy and the origin and variety of olives are rarely stated. The aim of this research was to validate a simple and rapid screening method for oleuropein determination in olive leaf dietary supplements. A matrix blank was prepared by removal of oleuropein from a mixture of dietary supplements and the matrix was then spiked with known concentrations to create a spiked matrix calibration curve in the range 5 - 40% oleuropein. Five replicate extractions and analyses of the matrix standards were carried out over 10 days. Precision was less than 6% RSD and linearity was demonstrated by the Fischer test. Extraction recovery was > 90% and there was a strong linear relationship between authentic and matrix standards. All tested products conformed to the label claim which was strongly correlated with total polyphenols measured by the Folin-Ciocalteau method. Antioxidant activity was measured by the DPPH assay and was found to be strongly correlated with total phenol content and oleuropein concentration.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".