The therapeutic effect of erbium pixel laser combined with silicone gel to prevent of postoperative facial scar
Bibliographic record
Abstract
Objective To observe the effect of facial scars were treated with erbium pixel laser combined with silicone gel.Methods The treatment group of 35 cases,within one month after facial wound healing begin the pixel erbium laser treatment,1 times a month,a total of five times,use silicon gel at the same time.The control group were 41 cases,only use the silicone gel,the same way as the treatment group.After 6 months treatment,Vancouver Scar scale(VSS) as the basis to evaluate the therapeutic effects were compared two groups.Results The mean total score on scar : treatment group was 3.43±1.945,control group was 4.37 ±1.593,t=-2.310,P0.05;the mean score on scar color: treatment group was 1.09 ±0.919,control group was 1.78 ±0.881,t =-3.359,P 0.05.Conclusion Erbium pixel laser combined with silicone gel to prevent facial scar effect in 6 months after operation is better than only using silicon gel,especially the scar color is better than single use of silicone gel.
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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) | 0.001 | 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".