A randomized, triple‐blind, placebo‐controlled, parallel study to evaluate the efficacy of a freshwater marine collagen on skin wrinkles and elasticity
Bibliographic record
Abstract
BACKGROUND: Collagen is the primary component in human skin. With age, there is loss of skin elasticity and collagen, resulting in wrinkle formation and reduction in skin appearance. AIMS: The objective of this randomized, triple-blind, placebo-controlled study was to evaluate the safety and efficacy of a hydrolyzed marine collagen (Vinh Wellness Collagen, VWC) on aspects of skin health and quality in women between 45 and 60 years of age. PATIENTS/METHODS: , and Skin Quality Visual Analogue Scale. Outcomes were assessed at weeks 0 (baseline), 6, and 12. RESULTS: After 12 weeks, participants supplemented with VWC had a significant 35% reduction in wrinkle score (P = .035) from baseline. Participants in the VWC group showed a 24% greater reduction in wrinkles on the right side of the face than those on placebo. A planned subgroup analysis based on age showed women 45-54 years had a significant 20% and 10% improvement in cheek skin elasticity from baseline to week 6 (P = .016) and 12 (P = .022), respectively. At week 12, participants in the VWC group reported greater percentage improvements in overall skin score (9%) and wrinkle (15%), elasticity (23%), hydration (14%), radiance (22%), and firmness (25%) scores vs placebo. CONCLUSION: Supplementation with VWC was found to be safe and well-tolerated. The results of this study support the use of fish-derived hydrolyzed collagen for the improvement of skin health in an aging population.
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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) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".