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Striae treated by a novel combination treatment – sand abrasion and a patent mixture containing 15% trichloracetic acid followed by 6–24 hrs of a patent cream under plastic occlusion

2003· article· en· W2042176711 on OpenAlexaff
Maurice Adatto, Philippe Deprez

Bibliographic record

VenueJournal of Cosmetic Dermatology · 2003
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsSKiN Health
Fundersnot available
KeywordsAbrasion (mechanical)MedicineOcclusionAbdomenDermatologySurgeryMaterials science

Abstract

fetched live from OpenAlex

BACKGROUND: Striae are a common cosmetic problem, especially for women. Little has been published about chemical peel treatment of striae. OBJECTIVE: To recount 5 years experience of striae treated by a novel combination treatment--sand abrasion and a patent mixture containing 15% trichloracetic acid followed by 6-24 h of a patent cream under plastic occlusion. MATERIALS AND METHODS: Sixty-nine females of various phototypes, aged 14-63 years, were treated at various anatomical sites: abdomen (43), lateral thighs (11), breasts (4), back (3), waist (3) and others (5). Striae of all types: fresh, old, mild and severe, were treated. Average follow up was 18 months. RESULTS: After 1-8 treatments (median 4.2), appearance of the striae improved by 70%. Results were best in fresher and more superficial striae. CONCLUSIONS: A novel combination treatment is reported which safely, predictably and effectively improved striae in all skin types.

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)0.000
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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)0.0040.001

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 head0.043
GPT teacher head0.294
Teacher spread0.251 · 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

Citations27
Published2003
Admission routes1
Has abstractyes

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