MétaCan
Menu
Back to cohort
Record W3037242855 · doi:10.1111/pde.13093

Addendum Guidelines for the Prevention of Peanut Allergy in the United States: Report of the National Institute of Allergy and Infectious Diseases–Sponsored Expert Panel

2017· article· en· W3037242855 on OpenAlex
Alkis Togias, Susan F. Cooper, Maria L. Acebal, Amal Assa’ad, James R. Baker, Lisa A. Beck, Julie Block, Carol Byrd‐Bredbenner, Edmond S. Chan, Lawrence F. Eichenfield, David M. Fleischer, George J. Fuchs, Glenn T. Furuta, Matthew Greenhawt, Ruchi S. Gupta, Michele Habich, Stacie M. Jones, Kari Keaton, Antonella Muraro, Marshall Plaut, Lanny J. Rosenwasser, Daniel Rotrosen, Hugh A. Sampson, Lynda C. Schneider, Scott H. Sicherer, Robert Sidbury, Jonathan M. Spergel, David R. Stukus, Carina Venter, Joshua A. Boyce

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePediatric Dermatology · 2017
Typearticle
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsBC Children's HospitalUniversity of British Columbia
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of HealthNational Peanut BoardDartmouth CollegeAimmune TherapeuticsDanoneMead Johnson NutritionTeva Pharmaceutical IndustriesImmune Tolerance NetworkAgency for Healthcare Research and QualityAcademy of Nutrition and DieteticsSanofiAstellas PharmaMylanGlaxoSmithKlinePfizer
KeywordsPeanut allergyMedicineFood allergyAllergyEnvironmental healthFamily medicineEgg allergyPediatricsImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: Food allergy is an important public health problem because it affects children and adults, can be severe and even life-threatening, and may be increasing in prevalence. Beginning in 2008, the National Institute of Allergy and Infectious Diseases, working with other organizations and advocacy groups, led the development of the first clinical guidelines for the diagnosis and management of food allergy. A recent landmark clinical trial and other emerging data suggest that peanut allergy can be prevented through introduction of peanut-containing foods beginning in infancy. OBJECTIVES: Prompted by these findings, along with 25 professional organizations, federal agencies, and patient advocacy groups, the National Institute of Allergy and Infectious Diseases facilitated development of addendum guidelines to specifically address the prevention of peanut allergy. RESULTS: The addendum provides three separate guidelines for infants at various risk levels for the development of peanut allergy and is intended for use by a wide variety of health care providers. Topics addressed include the definition of risk categories, appropriate use of testing (specific IgE measurement, skin prick tests, and oral food challenges), and the timing and approaches for introduction of peanut-containing foods in the health care provider's office or at home. The addendum guidelines provide the background, rationale, and strength of evidence for each recommendation. CONCLUSIONS: Guidelines have been developed for early introduction of peanut-containing foods into the diets of infants at various risk levels for peanut allergy.

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.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.225
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.090
GPT teacher head0.378
Teacher spread0.288 · 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