MétaCan
Menu
Back to cohort
Record W4376891061 · doi:10.3390/jpm13050835

ARIA Care Pathways 2019: Next-Generation Allergic Rhinitis Care and Allergen Immunotherapy in Malaysia

2023· review· en· W4376891061 on OpenAlexaff
Amir Hamzah Abdul Latiff, Salina Husain, Baharudin Abdullah, Palaniappan Suppiah, Vincent Y. F. Tan, Tang Ing Ping, Kent Woo, Yoke‐Yeow Yap, Claus Bachert, Holger J. Schünemann, Anna Bedbrook, Jean Bousquet

Bibliographic record

VenueJournal of Personalized Medicine · 2023
Typereview
Languageen
FieldMedicine
TopicAllergic Rhinitis and Sensitization
Canadian institutionsMcMaster University
FundersGlaxoSmithKline
KeywordsMedicineContext (archaeology)GuidelineHealth carePatient EmpowermentAsthmaEmpowermentAllergen immunotherapyImmunologyAllergyAllergen

Abstract

fetched live from OpenAlex

An increase in the prevalence of allergic rhinitis (AR) worldwide presents a significant burden to the health care system. An initiative was started in Europe designated as Allergic Rhinitis and Its Impact on Asthma (ARIA) to develop internationally applicable guidelines by utilising an evidence-based approach to address this crucial issue. The efforts are directed at empowerment of patients for self-management, the use of digital mobile technology to complement and personalise treatment, and establishment of real-life integrated care pathways (ICPs). This guideline includes aspects of patients' and health care providers' management and covers the main areas of treatment for AR. The model provides better real-life health care than the previous traditional models. This review summarises the ARIA next-generation guideline in the context of the Malaysian health care system.

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)0.002
metaresearch head score (Gemma)0.003
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: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.105
GPT teacher head0.342
Teacher spread0.237 · 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
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

Citations11
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Personalized MedicineSame topicAllergic Rhinitis and SensitizationFrench-language works237,207