MétaCan
Menu
Back to cohort
Record W4390512633 · doi:10.17352/2455-8605.000049

The efficacy of single treatment of fractionated CO2 laser to improve scars in rhinoplasty

2023· article· en· W4390512633 on OpenAlexaboutno aff
Shah Anil R, Meter Sarah Van

Bibliographic record

VenueInternational Journal of Dermatology and Clinical Research · 2023
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsScarsMedicineSurgeryVascularityRhinoplastyDermabrasionNose

Abstract

fetched live from OpenAlex

Background: The formation of scars is fairly inevitable after open rhinoplasty and alar base procedures. Oftentimes, patients exhibit insecurities or discomfort at the appearance of these scars. CO2 laser resurfacing has been proposed as an effective treatment to minimize the appearance of surgical scars. Objective: To demonstrate the effectiveness of fractionated CO2 laser in the minimization of the appearance of surgical scars. Methods: Retrospective analysis of a rhinoplasty surgeon’s database as well as blinded grading of 54 consecutive alar wedge scars using Vancouver Scar Scales. Results: No complications were seen with the use of fractionated CO2 lasers as a treatment on rhinoplasty scars. No difference was seen in scar appearance, including scar height, vascularity, pliability, and scar height after one treatment of CO2 laser. Conclusion: A single treatment of fractionated CO2 laser does not improve scars. Multiple sessions of fractionated CO2 laser could be a more effective treatment for the appearance of surgical 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.119
Threshold uncertainty score0.292

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.134
GPT teacher head0.518
Teacher spread0.384 · 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 teacher head, 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Dermatology and Clinical ResearchSame topicDermatologic Treatments and ResearchFrench-language works237,207