Safety and Efficacy of Botulinum toxin Toxin A combined with Radiofrequency Home- Device for Rejuvenation
Bibliographic record
Abstract
Abstract Botulinum toxin type A (BoNT-A) is confirmed to be effective and one of the most widely used cosmetic injection techniques for treating dynamic wrinkles. In principle, it has been proven to reduce wrinkles by inhibiting the release of acetylcholine from presynaptic nerve endings, causing chemical denervation and resultant muscle paresis [1-3]. To maintain the effects continuously, continuous injections at regular intervals are required because the neuronal and muscular changes that occur after BoNT-A administration are completely reversible, and the duration of maintenance is limited [4]. Furthermore, it can only improve dynamic wrinkles, not wrinkles and lines that have already formed. In recent times, many studies have reported clinical benefits of radiofrequency (RF) home-use devices in reducing wrinkles on the skin by heating dermal tissue and firming collagen fibers[5-7]. These devices are highly suitable for daily skincare maintenance or for prolonging the duration of results after undergoing aesthetic procedures, with their safety and efficacy well-established [8, 9].In this study, we aimed to assess the safety and efficacy of home-use RF device combined with botulinum toxin A treatment for periocular wrinkles.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.003 | 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".