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Record W3187490907 · doi:10.21608/bjas.2019.187129

Different Treatment Modalities in Treatment of Hypertrophic Scar (Comparative study)

2019· article· en· W3187490907 on OpenAlexaboutno aff
Sh.H. Abdel-Rahman, A.M. Hamed, M. Darwish

Bibliographic record

VenueBenha Journal of Applied Sciences · 2019
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsHypertrophic scarTreatment modalityModalitiesMedicineInternal medicineSurgerySociology

Abstract

fetched live from OpenAlex

Hypertrophic scars are dermal fibroproliferative disorders that typically develop after a skin injury heals. They can cause physical, psychological, and cosmetic problems. The management of such scars remains a matter of debate due to lack of effective treatment methods and the inability to prevent recurrences. The aim of this work is to assess the effectiveness of efficacy and safety of ND-YAG laser alone or in combination with intralesional injection of steroid. This prospective clinical study included twenty patients with hypertrophic scars divided equally in to two groups. All patients received Nd:Yag laser session once a month for three months with a follow-up period of six months. The second group recieved intralesional injection of steroid after each laser session. Therapeutic satisfaction of the patient and physician were recorded. Lesions were assessed for erythema, pigmentation, height and pliability using Vancouver Scar Scale as well as itching and pain.

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)0.000
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 score0.145
Threshold uncertainty score0.309

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 head0.100
GPT teacher head0.373
Teacher spread0.273 · 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
Published2019
Admission routes1
Has abstractyes

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