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Record W3184763414 · doi:10.1016/j.jaip.2021.06.057

Establishing Amoxicillin Allergy in Children Through Direct Graded Oral Challenge (GOC): Evaluating Risk Factors for Positive Challenges, Safety, and Risk of Cross-Reactivity to Cephalosporines

2021· article· en· W3184763414 on OpenAlexafffund
Rutherford Exius, Sofianne Gabrielli, Elissa M. Abrams, Andrew O’Keefe, Jennifer L. P. Protudjer, Elana Lavine, Tracy Pitt, Adelle Atkinson, Thomas Eiwegger, Christine McCusker, Moshe Ben‐Shoshan

Bibliographic record

VenueThe Journal of Allergy and Clinical Immunology In Practice · 2021
Typearticle
Languageen
FieldMedicine
TopicDrug-Induced Adverse Reactions
Canadian institutionsSt. Joseph's HospitalSickKids FoundationHumber River Regional HospitalHospital for Sick ChildrenQueen's UniversityMontreal Children's HospitalUniversity of TorontoGeorge & Fay Yee Centre for Healthcare InnovationChildren's Hospital Research Institute of ManitobaResearch ManitobaUniversity of ManitobaChildren’s Health Research InstituteMemorial University of NewfoundlandUniversity of British ColumbiaMcGill University Health Centre
FundersInstitute of Infection and ImmunityCanadian Institutes of Health Research
KeywordsMedicineAmoxicillinReactivity (psychology)AllergyRisk assessmentEnvironmental healthPediatricsAntibioticsImmunologyAlternative medicineComputer securityPathology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.006
metaresearch head score (Gemma)0.030
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.649
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.070
GPT teacher head0.411
Teacher spread0.341 · 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 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

Citations44
Published2021
Admission routes2
Has abstractno

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