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Diagnosis and Management of Cutaneous Tinea Infections

2019· article· en· W2964152163 on OpenAlexaff
Taylor E. Woo, Ranjani Somayaji, Richard M. Haber, Laurie Parsons

Bibliographic record

VenueAdvances in Skin & Wound Care · 2019
Typearticle
Languageen
FieldMedicine
TopicNail Diseases and Treatments
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineDermatophyteDermatologyEpidemiologyTrichophytonSkin infectionTinea capitisPathologyAntifungalStaphylococcus aureus

Abstract

fetched live from OpenAlex

GENERAL PURPOSE: To provide information about the epidemiology, clinical features, and management of cutaneous tinea infections. TARGET AUDIENCE: This continuing education activity is intended for physicians, physician assistants, nurse practitioners, and nurses with an interest in skin and wound care. LEARNING OBJECTIVES/OUTCOMES: After completing this continuing education activity, you should be better able to:1. Summarize the epidemiology related to cutaneous tinea infections.2. Describe the clinical features of cutaneous tinea infections.3. Identify features related to the diagnosis and management of cutaneous tinea infections. ABSTRACT: Dermatophyte or tinea infection refers to a group of superficial fungal infections of the hair, skin, and nails. Tinea infections are most commonly caused by fungi of the genus Trichophyton, Microsporum, or Epidermophyton. Cutaneous manifestations of tinea infections are seen worldwide and classified based on the affected body site. The diagnosis of these conditions is complicated by morphologic variations in presentation and overlap with other common infectious and noninfectious entities. As a result, diagnosis and appropriate management of these conditions are essential to avoid patient morbidity. This case-based review summarizes the epidemiology, relevant clinical features, microbiology, and management considerations for commonly encountered tinea infections.

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 score0.175
Threshold uncertainty score0.265

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.005
GPT teacher head0.285
Teacher spread0.280 · 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

Citations18
Published2019
Admission routes1
Has abstractyes

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