MétaCan
Menu
Back to cohort
Record W3207588227 · doi:10.1183/13993003.02730-2021

Global Initiative for Asthma Strategy 2021: executive summary and rationale for key changes

2021· review· en· W3207588227 on OpenAlexaff
Helen K. Reddel, Leonard B. Bacharier, Eric D. Bateman, Christopher E. Brightling, Guy Brusselle, Roland Buhl, Álvaro A. Cruz, Liesbeth Duijts, Jeffrey M. Drazen, J. Mark FitzGerald, Louise Fleming, Hiromasa Inoue, Fanny W.S. Ko, Jerry A. Krishnan, Mark L Levy, Jiangtao Lin, Kevin Mortimer, Paulo Márcio Pitrez, Aziz Sheikh, Arzu Yorgancıoğlu, Louis‐Philippe Boulet

Bibliographic record

VenueEuropean Respiratory Journal · 2021
Typereview
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversité LavalInstitut universitaire de cardiologie et de pneumologie de QuébecUniversity of British Columbia
FundersNational Institute for Health and Care Research
KeywordsMedicineExecutive summaryUnderpinningKey (lock)AsthmaIntensive care medicineImmunology

Abstract

fetched live from OpenAlex

<b>The GINA Strategy Report provides clinicians with an annually updated evidence-based strategy for asthma management and prevention. This article summarizes key recommendations from GINA 2021, and the evidence underpinning the new changes.</b>https://bit.ly/3FZblIS

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)0.010
metaresearch head score (Gemma)0.010
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.018
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.006
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0020.002
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0180.013

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 head0.364
Teacher spread0.260 · 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

Citations540
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Respiratory JournalSame topicAsthma and respiratory diseasesFrench-language works237,207