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Record W4379615845 · doi:10.1016/j.jaci.2023.05.019

Updated guidance regarding the risk of allergic reactions to COVID-19 vaccines and recommended evaluation and management: A GRADE assessment and international consensus approach

2023· review· en· W4379615845 on OpenAlexafffund
Matthew Greenhawt, Timothy E. Dribin, Elissa M. Abrams, Marcus Shaker, Derek K. Chu, David B.K. Golden, Cem Akin, Aikaterini Anagnostou, Faisal ALMuhizi, Waleed Alqurashi, Peter D. Arkwright, James L. Baldwin, Aleena Banerji, Philippe Bégin, Moshe Ben‐Shoshan, Jonathan A. Bernstein, Theresa Bingemann, Carsten Bindslev‐Jensen, Kim Blumenthal, Aideen Byrne, J. Cahill, Scott B. Cameron, Dianne E. Campbell, Ronna L. Campbell, Michael Cavender, Edmond S. Chan, R. Sharon Chinthrajah, Pasquale Comberiati, Jacqueline J. Eastman, Anne K. Ellis, David M. Fleischer, Adam Fox, Pamela A. Frischmeyer‐Guerrerio, Rémi Gagnon, Lene H. Garvey, Mitchell H. Grayson, Ghislaine Annie Clarisse Isabwe, Nicholas Hartog, David Hendron, Caroline C. Horner, Johnathan O'B Hourihane, E.A. Ba, Manstein Kan, Blanka Kaplan, Constance H. Katelaris, Harold Kim, John M. Kelso, David A. Khan, David M. Lang, Dennis K. Ledford, Michael Levin, Phil Lieberman, Richard Loh, Douglas P. Mack, Bruce Mazer, K Mody, G. Mosnaim, Daniel Munblit, S. Shahzad Mustafa, Anil Nanda, Richard Nathan, John Oppenheimer, Iris M. Otani, Miguel Park, Ruby Pawankar, Kirsten P. Perrett, Jonny Peter, Matthieu Picard, Mitchell M. Pitlick, Allison Ramsey, Trine Holm Rasmussen, Melinda M. Rathkopf, Hari Reddy, Kara Robertson, Pablo Rodríguez del Río, Stephen Sample, Ajay Sheshadri, Javed Sheik, Sayantani Sindher, Jonathan M. Spergel, Cosby A. Stone, David R. Stukus, Mimi L.K. Tang, James M. Tracy, Paul Turner, Timothy K. Vander Leek, Dana Wallace, Julie Wang, Susan Wasserman, David Weldon, Anna R. Wolfson, Margitta Worm, Mona‐Rita Yacoub

Bibliographic record

VenueJournal of Allergy and Clinical Immunology · 2023
Typereview
Languageen
FieldMedicine
TopicAllergic Rhinitis and Sensitization
Canadian institutionsUniversité de MontréalStollery Children's HospitalHôpital Maisonneuve-RosemontQueen's UniversityBC Children's HospitalUniversity of British ColumbiaFraser HealthUniversity of AlbertaMcGill UniversityUniversity of OttawaCentre Hospitalier Universitaire Sainte-JustineMcMaster UniversityMcMaster University Medical CentreUniversity of ManitobaSt. Joseph’s Healthcare HamiltonSt Joseph's Health CareUniversity of CalgaryImpactWestern UniversityMontreal Children's Hospital
FundersNational Institute of Allergy and Infectious DiseasesSanofi GenzymeGenentechAgency for Healthcare Research and QualityLEO PharmaBausch HealthPfizerIncyteAmerican Lung AssociationNational Peanut BoardBioCrystNational Institutes of HealthRegeneron PharmaceuticalsMylanCelldex TherapeuticsJapan Association for Chemical InnovationAmgenAustralasian Society of Clinical Immunology and AllergyMcGill UniversityDanoneAmerican Academy of Allergy, Asthma and Immunology FoundationMassachusetts General HospitalNational Center for Advancing Translational SciencesTeva Pharmaceutical IndustriesWorld Health OrganizationSanofiAimmune TherapeuticsCSL BehringAstraZenecaAstellas PharmaFood Allergy Research and EducationAsthma and Allergy Foundation of AmericaGlaxoSmithKline
KeywordsMedicineVaccinationAllergyPandemicImmunologyIntensive care medicinePediatricsCoronavirus disease 2019 (COVID-19)DiseaseInfectious disease (medical specialty)Internal medicine

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 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)0.014
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.020
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.007
Bibliometrics0.0070.004
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0040.002
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0050.002

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 head0.169
GPT teacher head0.461
Teacher spread0.293 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations20
Published2023
Admission routes2
Has abstractno

Explore more

Same venueJournal of Allergy and Clinical ImmunologySame topicAllergic Rhinitis and SensitizationFrench-language works237,207