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Record W2905739553 · doi:10.1111/ijd.14346

Global perspectives for the management of onychomycosis

2018· review· en· W2905739553 on OpenAlexaff
Aditya Gupta, Rachel Mays, Sarah G. Versteeg, Bianca Maria Piraccini, Anita Takwale, Avner Shemer, Meir Babaev, Chander Grover, Nilton Gióia Di Chiacchio, Paulo R. Taborda, Valeria Brega Alvares Taborda, Neil H. Shear, Vincent Piguet, Antonellá Tosti

Bibliographic record

VenueInternational Journal of Dermatology · 2018
Typereview
Languageen
FieldMedicine
TopicNail Diseases and Treatments
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreMediprobe Research (Canada)Women's College HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineNail diseaseIntensive care medicinePerspective (graphical)TerbinafineGovernment (linguistics)Disease managementDermatologyDiseaseAntifungalItraconazolePathologyParonychia

Abstract

fetched live from OpenAlex

Onychomycosis is a fungal nail infection caused by dermatophytes, nondermatophyte molds, and yeasts. This difficult-to-treat chronic infection has a tendency to relapse despite treatment. This paper aims to offer a global perspective on onychomycosis management from expert physicians from around the world. Overall, the majority of experts surveyed used systemic, topical, and combination treatments approved in their countries and monitored patients based on the product insert or government recommendations. Although the basics of treating onychomycosis were similar between countries, slight differences in onychomycosis management between countries were found. These differences were mainly due to different approaches to adjunctive therapy, rating the severity of disease and use of prophylaxis treatment. A global perspective on the treatment of onychomycosis provides a framework of success for the committed clinician with appreciation of how onychomycosis is managed worldwide.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.002

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 head0.044
GPT teacher head0.429
Teacher spread0.385 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations67
Published2018
Admission routes1
Has abstractyes

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