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Record W2996692926 · doi:10.1002/9781119142812.ch59

Scabies and Pseudoscabies

2019· other· en· W2996692926 on OpenAlexaff
Wingfield Rehmus, Julie Prendiville

Bibliographic record

VenueHarper's Textbook of Pediatric Dermatology · 2019
Typeother
Languageen
FieldMedicine
TopicDermatological diseases and infestations
Canadian institutionsBC Children's HospitalUniversity of British Columbia
Fundersnot available
KeywordsIvermectinSarcoptes scabieiScabiesDermatologyInfestationMedicineBiologyVeterinary medicine

Abstract

fetched live from OpenAlex

Scabies is caused by infestation of the skin by Sarcoptes scabiei var. hominis. It affects all age groups and is a worldwide disease. Clinical features appear several weeks after exposure, and are associated with pruritus. Burrows, excoriations, vesicles, papules and nodules are seen on physical examination. Infested individuals are at risk of secondary bacterial infection. Diagnosis is often made clinically, but can be confirmed by performing a scabies preparation and/or dermoscopy. Topical therapy is the mainstay of treatment and should be utilized by all household and other contacts. For severe infestations, oral ivermectin is an alternative therapy. The term pseudoscabies is used to describe a skin eruption caused by mites for which, unlike scabies, humans are not the normal host. Bird, rodent and dog mites are most commonly implicated in children. Pseudoscabies is characterized clinically by nonspecific pruritic papules on exposed skin. Diagnosis requires a high degree of clinical suspicion, as the offending mites are barely visible to the human eye. Treatment depends primarily upon the identification and removal (or treatment) of the source of contact.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.053
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.012
GPT teacher head0.265
Teacher spread0.253 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2019
Admission routes1
Has abstractyes

Explore more

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