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Record W1577736429 · doi:10.4103/0970-0358.146596

Effect of intense pulsed light on immature burn scars: A clinical study

2014· article· en· W1577736429 on OpenAlexaboutno aff
Arindam Sarkar, Yatindra Kumar Dewangan, Jayanta Bain, Pritha Rakshit, Krishnanand Dhruw, Sandip Basu, Jayanta Saha, Bijay Kumar Majumdar

Bibliographic record

VenueIndian Journal of Plastic Surgery · 2014
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineScarsVascularityIntense pulsed lightGrading scaleSurgeryDermatology

Abstract

fetched live from OpenAlex

INTRODUCTION: As intense pulsed light (IPL) is widely used to treat cutaneous vascular malformations and also used as non-ablative skin rejunuvation to remodel the skin collagen. A study has been undertaken to gauze the effect of IPL on immature burn scars with regard to vascularity, pliability and height. MATERIALS AND METHODS: This study was conducted between June 2013 and May 2014, among patients with immature burn scars that healed conservatively within 2 months. Photographic evidence of appearance of scars and grading and rating was done with Vancouver Scar Scale parameters. Ratings were done for both case and control scar after the completion of four IPL treatment sessions and were compared. RESULTS: Out of the 19 cases, vascularity, pliability and height improved significantly (P < 0.05) in 13, 14 and 11 scars respectively following IPL treatment. CONCLUSIONS: Intense pulsed light was well-tolerated by patients, caused good improvement in terms of vascularity, pliability, and height of immature burn scar.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.023
GPT teacher head0.352
Teacher spread0.329 · 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 designNon-randomized trial
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

Citations14
Published2014
Admission routes1
Has abstractyes

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