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Record W7129599729 · doi:10.1080/14764172.2026.2633119

The role of fractional CO <sub>2</sub> laser therapy in post-surgical skin cancer scarring

2025· article· en· W7129599729 on OpenAlexaboutno aff
Lluís Corbella-Bagot, Agustí Toll-Abelló, Paula Aguilera-Peiró, Alejandra Sandoval-Clavijo

Bibliographic record

VenueJournal of Cosmetic and Laser Therapy · 2025
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsScarsSkin cancerReduction (mathematics)CancerLaser therapyLaserRetrospective cohort study

Abstract

fetched live from OpenAlex

Scars from skin cancer surgery impact patients’ quality of life. In recent years, fractional CO2 (fCO2) laser has been used for scar improvement. A single-center retrospective study (n = 22) was conducted to evaluate the safety and efficacy of the fCO2 laser in improving the aesthetic outcome of post-surgical skin cancer scars, using the validated Vancouver Scar Scale (VSS). We obtained a mean VSS reduction of 44.5% and an absolute decrease of 2.77 points (p < .001). Statistically significant improvements were observed in all VSS parameters except for pigmentation. No significant correlation was found between time since surgery and reduction in VSS. Fractional CO2 laser is a safe and effective approach for improving surgical scars following skin cancer treatment. Its efficacy is not limited to early scars.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.012
GPT teacher head0.325
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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