MétaCan
Menu
Back to cohort

Early Postoperative Treatment of Thyroidectomy Scars Using a Fractional Carbon Dioxide Laser

2011· article· en· W2044000149 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueDermatologic Surgery · 2011
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineScarsThyroidectomySurgeryAblative caseCarbon dioxide laserThyroidLaserLaser surgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Ablative carbon dioxide fractional laser systems (CO(2) FS) have been effectively used to improve the appearance of scarring after surgical procedures, but an optimal treatment time has not been established. OBJECTIVE: To evaluate the efficacy and safety of CO(2) FS in early postoperative thyroidectomy scars. METHODS: Twenty-three Korean women with thyroidectomy scars were enrolled in this study. All patients underwent a single session of two passes of a CO(2) FS with a pulse energy setting of 50 mJ and a density of 100 spots/cm(2) 2 to 3 weeks after surgery. RESULTS: Mean Vancouver Scar Scale (VSS) scores were statistically significantly lower after laser treatment. Three months after CO(2) FS treatment of thyroidectomy scarring, 12 of 23 participants showed clinical improvement of more than 51% from 2 to 3 weeks after surgery. The mean grade of clinical improvement based on independent clinical assessment was 2.6 ± 0.9. CONCLUSION: Early postoperative CO(2) FS treatment of thyroidectomy scars is effective and safe.

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.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.133
Threshold uncertainty score0.613

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.106
GPT teacher head0.317
Teacher spread0.211 · 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