Fractional <scp> CO <sub>2</sub> </scp> laser to improve noticeable scars after skin cancer surgery: An appraisal by the patients, laypersons, and experts
Bibliographic record
Abstract
Ablative fractionated carbon dioxide (fCO2) laser may be a useful tool to improve noticeable scars after skin cancer surgery. Therefore we evaluated 40 patients who have been treated with fCO2 laser for facial scars after skin cancer surgery. This retrospective study is based on blinded evaluation of pre- and postoperative photographs. Patients (n = 40), laypersons (n = 5) and experts (n = 5) evaluated the esthetics and the Vancouver scar scale as primary endpoints. Secondary endpoints included patient satisfaction and treatment safety. Patients, laypersons and experts consistently assessed a significant improvement of scar quality and appearance after fCO2 laser treatment, which was paralleled by high patient satisfaction. In conclusion, ablative fCO2 laser is effective in improving noticeable postsurgical scars. Patients are highly satisfied with post-laser results.
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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 | 0.002 |
| 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".