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Record W2677331635 · doi:10.2217/pgs-2017-0035

Rationale and Design of the Multiethnic Pharmacogenomics in Childhood Asthma Consortium

2017· article· en· W2677331635 on OpenAlexaff
Niloufar Farzan, Susanne J. H. Vijverberg, Anand Kumar Andiappan, Lambang Arianto, Vojko Berce, Natalia Blanca‐López, Hans Bisgaard, Klaus B⊘nnelykke, Esteban G. Burchard, Paloma Campo, Glorisa Canino, Bruce Carleton, Juan C Celedón, Fook Tim Chew, Wen Chin Chiang, Michelle M. Cloutier, Denis Daley, Herman T. den Dekker, F. Nicole Dijk, Liesbeth Duijts, Carlos Flores, Erick Forno, Daniel B. Hawcutt, Natalia Hernandez‐Pacheco, Johan C. de Jongste, Michael Kabesch, Gerard H. Koppelman, Vangelis G. Manolopoulos, Erik Melén, Somnath Mukhopadhyay, Sara Nilsson, Maria Pino‐Yanes, Munir Pirmohamed, Uros Potočnki, Jan A. M. Raaijmakers, Katja Repnik, Maximilian Schieck, Yang Yie Sio, Rosalind L. Smyth, Csaba Szalai, Kelan G. Tantisira, Steve Turner, Marc P. van der Schee, Katia Verhamme, Anke H. Maitland‐van der Zee

Bibliographic record

VenuePharmacogenomics · 2017
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversity of British Columbia
FundersMedical Research CouncilStockholms Läns LandstingStichting Astma BestrijdingHjärt-LungfondenNational Institutes of HealthNational Heart, Lung, and Blood InstituteVetenskapsrådetKarolinska InstitutetLundbeckfondenEuropean CommissionInstituto de Salud Carlos IIINational Institute for Health and Care Research
KeywordsPharmacogenomicsAsthmaMedicinePharmacogeneticsPharmacologyInternal medicineGeneticsBiologyGenotype

Abstract

fetched live from OpenAlex

AIM: International collaboration is needed to enable large-scale pharmacogenomics studies in childhood asthma. Here, we describe the design of the Pharmacogenomics in Childhood Asthma (PiCA) consortium. MATERIALS & METHODS: Investigators of each study participating in PiCA provided data on the study characteristics by answering an online questionnaire. RESULTS: A total of 21 studies, including 14,227 children/young persons (58% male), from 12 different countries are currently enrolled in the PiCA consortium. Fifty six percent of the patients are Caucasians. In total, 7619 were inhaled corticosteroid users. Among patients from 13 studies with available data on asthma exacerbations, a third reported exacerbations despite inhaled corticosteroid use. In the future pharmacogenomics studies within the consortium, the pharmacogenomics analyses will be performed separately in each center and the results will be meta-analyzed. CONCLUSION: PiCA is a valuable platform to perform pharmacogenetics studies within a multiethnic pediatric asthma population.

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 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)0.152
metaresearch head score (Gemma)0.109
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.152
Threshold uncertainty score0.803

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1520.109
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.006
Science and technology studies0.0060.004
Scholarly communication0.0050.003
Open science0.0060.009
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0110.003

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 head0.039
GPT teacher head0.313
Teacher spread0.274 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations31
Published2017
Admission routes1
Has abstractyes

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