A serum containing vitamins C & E and a matrix‐repair tripeptide reduces facial signs of aging as evidenced by Primos® analysis and frequently repeated auto‐perception
Bibliographic record
Abstract
BACKGROUND: Allegations on the benefits of incorporating vitamin C, vitamin E, and combinations thereof in topical skincare formulations are mostly based on in vitro and ex vivo experiments and/or limited protocols of specific stress conditions (pollution, UV exposure, laser irradiation,…). OBJECTIVE: To evaluate the instrumentally measurable effects and quantitative consumer perceptions of a protective and reparative serum on a panel of volunteers under normal nonstressed conditions of use, employing FOITS technology and innovative self-assessment methods. METHOD: In an open-label study women of ≥40 years with visible signs of photoaging applied a serum comprising l-ascorbic acid USP (15% w/v), tocopheryl acetate USP, and 5 ppm palmitoyl tripeptide-38 to the face once daily for 56 days. Skin roughness and isotropy changes were evaluated on days 0, 28, and 56, visual instrumental evaluation of skin-tone parameters was assessed on days 0 and 56. Subjects completed self-assessment questionnaires every third day of the trial period for radiance, homogeneity, and wrinkle appearance. RESULTS: Skin-roughness parameters decreased significantly by 8%-9% (P < .05) and subjects experienced a significant increase in skin isotropy (P < .05). Photographic analysis revealed significant improvements in skin tone, with a 9% decrease in redness and 8% increase in homogeneity (P < .0001 for both), in excellent agreement with subjects' perception of significant improvements of radiance, complexion, and wrinkles. CONCLUSION: The study confirms statistically significant correlation between objectively measured and quantitative subjectively perceived benefits of the bespoke serum containing antioxidants and a matrix-restoring peptide.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".