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Record W4213330622 · doi:10.3410/f.735401227.793576499

Faculty Opinions recommendation of Pediatric toxic epidermal necrolysis treated successfully with infliximab.

2020· dataset· en· W4213330622 on OpenAlexaff
Michele Ramien

Bibliographic record

VenueFaculty Opinions – Post-Publication Peer Review of the Biomedical Literature · 2020
Typedataset
Languageen
FieldMedicine
TopicDrug-Induced Adverse Reactions
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsToxic epidermal necrolysisMedicineDermatologyInfliximabMycoplasma pneumoniaeHyperpigmentationTumor necrosis factor alphaSurgeryInternal medicinePneumonia

Abstract

fetched live from OpenAlex

Successful management of toxic epidermal necrolysis (TEN) with tumor necrosis factor-α inhibitors has been described in adults. We present a case of a 7-year-old boy with infection-associated TEN, diagnosed by typical clinical and histopathological features, most likely caused by Mycoplasma pneumoniae. Treatment with a single dose of infliximab 5 mg/kg intravenously on day 5 after the onset of symptoms was followed by cessation of all blister formation over 3 days and complete resolution within a week. Sequelae were mild, consisting of postinflammatory hyperpigmentation and dry eyes.© 2019 Wiley Periodicals, Inc. PMID: 30834560

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)0.001
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.206
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.006
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
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 head0.034
GPT teacher head0.344
Teacher spread0.311 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2020
Admission routes1
Has abstractyes

Explore more

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