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Record W4412459762 · doi:10.1016/j.jaip.2025.07.004

Intranasal Treatments for Allergic Rhinitis in Preschool- and School-Age Children: Network Meta-Analysis

2025· article· en· W4412459762 on OpenAlexaff
Sara Gil‐Mata, Rafael José Vieira, E Borowiack, Ewelina Sadowska, Antonio Bognanni, António Cardoso‐Fernandes, Henrique Ferreira-Cardoso, João Castro‐Teles, Juliana Soprani, Liliane Pinheiro, Manuel Marques‐Cruz, Miguel Campos-Lopes, Nuno Lourenço‐Silva, Renato Ferreira‐da‐Silva, Anna Bedbrook, Justyna Lityńska, Iván Chérrez-Ojeda, Ludger Klimek, Oliver Pfaar, Ricardo M. Fernandes, Alessandro Fiocchi, Mattia Giovannini, Désirée Larenas‐Linnemann, N. Pham‐Thi, Nikolaos Papadopoulos, Graham Roberts, Arunas Valiulis, Juan José Yepes-Núñez, Torsten Zuberbier, João Fonseca, Holger J. Schünemann, Bernardo Sousa‐Pinto

Bibliographic record

VenueThe Journal of Allergy and Clinical Immunology In Practice · 2025
Typearticle
Languageen
FieldMedicine
TopicAllergic Rhinitis and Sensitization
Canadian institutionsHôpital Charles-Le MoyneMcMaster UniversityHamilton Regional Laboratory Medicine Program
Fundersnot available
KeywordsMedicineMeta-analysisNasal administrationPediatricsMEDLINEImmunologyInternal 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 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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.747
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.046
GPT teacher head0.370
Teacher spread0.324 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
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
Published2025
Admission routes1
Has abstractno

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