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Record W2783329207 · doi:10.1111/pde.13391

Potassium iodide in refractory, recurrent pediatric Sweet syndrome: Guidance in dosing and monitoring

2018· article· en· W2783329207 on OpenAlexaff
Jennifer Aileen Tangtatco, Nhung Ho, Aaron M. Drucker, Catherine L. Forse

Bibliographic record

VenuePediatric Dermatology · 2018
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders
Canadian institutionsUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsMedicineRefractory (planetary science)DosingIodidePotassiumInternal medicinePediatricsChemistryInorganic chemistry

Abstract

fetched live from OpenAlex

We describe a 5-month-old boy with clinical and histopathologic presentation of Sweet syndrome. He responded to systemic corticosteroids, with multiple flares on tapering; potassium iodide was added, which provided complete resolution of Sweet syndrome. Potassium iodide has been used in only a few cases, and no standard dosage has been established in children. We discuss calculation of a pediatric dosage for potassium iodide in Sweet syndrome.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.276
Teacher spread0.263 · 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 designCase report
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

Citations5
Published2018
Admission routes1
Has abstractyes

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