Analytical Accuracy and Reliability of Commonly Used Nutritional Supplements in Prostate Disease
Bibliographic record
Abstract
PURPOSE: We determine the analytical accuracy and reliability of commonly used nutritional supplements for prostate disease by comparing the amounts of active ingredients of several brands of vitamin E, vitamin D, selenium, lycopene and saw palmetto. We also compared the amounts of active compound in different lots of the same brand to determine the consistency of the manufacturing process. MATERIALS AND METHODS: Samples purchased at pharmacies and specialty stores were sent for independent chemical analysis. The measured dose was compared to the stated dose on the product label. Analysis of variance was performed to test for significance in interlot reliability. RESULTS: Vitamin E (7 samples) and selenium (5) were within a range of -41% to +57% and -19% to +23% of the stated dosage, respectively. All vitamin D brands (4 samples) were within 15% of the stated dose. Saw palmetto (6 samples) were within a range -97% to +140% of the stated dosages with 3 containing less than 20% of the stated dosages. Lycopene brands were between -38% and +143% of stated dosages. Among the reliability assays 1 of 3 brands of vitamin E, 1 of 2 brands of selenium and 1 of 2 brands of saw palmetto demonstrated statistical differences in interlot dosage (p <0.0055, approximate 20% to 25% differences in dose). The 1 assayed form of vitamin D was reliable between lots. CONCLUSIONS: Commonly used nutritional supplements for prostate disease vary widely in measured dose. Saw palmetto demonstrated tremendous variability with some samples containing virtually no active ingredients. In contrast, the more regulated substances we measured, such as vitamins and minerals, demonstrated less variation.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".