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Record W4388578618

YCANTH<sup>TM</sup> (Cantharidin) Topical Solution.

2023· article· en· W4388578618 on OpenAlexaff
Aditya K. Gupta, Avantika Mann, Kimberly Vincent, William Abramovits

Bibliographic record

VenuePubMed · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPoxvirus research and outbreaks
Canadian institutionsMediprobe Research (Canada)University of Toronto
Fundersnot available
KeywordsCantharidinMedicineMolluscum contagiosumDermatologyAdverse effectPharmacology
DOInot available

Abstract

fetched live from OpenAlex

(cantharidin) topical solution has been approved recently for the treatment of molluscum contagiosum (MC) in children (aged ≥2 years) and adults. It works by activating serine proteases that lead to blistering and inflammation, promoting shedding of infected cells and viral clearance. In two phase-3, randomized, double-blind, vehicle-controlled trials of similar design, VP-102 (a drug-device combination, containing cantharidin 0.7% w/v and inactive ingredients, such as gentian violet, acetone, and denatonium benzoate, administered with an applicator) was investigated for the treatment of MC. VP-102 and vehicle were applied topically once every 21 days until complete clearance of lesions was observed, or for up to four treatments. Cantharidin demonstrated efficacy in achieving the primary outcome, at day 84/visit 4 (Cantharidin Application in Molluscum Patients [CAMP-1], VP-102: 46% [73/160], vehicle: 18% [19/106]; and CAMP-2, VP-102: 54% [81/150], vehicle: 13% [15/112]). Common adverse events were mild to moderate, such as lesions at the site of application, pruritus, and pain. The recommended regimen of cantharidin topical solution is its application once every 21 days until complete clearance of lesions is observed, or up to four treatments.

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)0.000
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: Other · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.002

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 head0.037
GPT teacher head0.256
Teacher spread0.219 · 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
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

Citations0
Published2023
Admission routes1
Has abstractyes

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