MétaCan
Menu
Back to cohort
Record W2129917430 · doi:10.1186/s40413-015-0080-1

2015 update of the evidence base: World Allergy Organization anaphylaxis guidelines

2015· article· en· W2129917430 on OpenAlexaff
F. Estelle R. Simons, Motohiro Ebisawa, Mario Sánchez‐Borges, Bernard Yu‐Hor Thong, Margitta Worm, Luciana Kase Tanno, Richard F. Lockey, Yehia El‐Gamal, Simon G.A. Brown, Hae‐Sim Park, Aziz Sheikh

Bibliographic record

VenueWorld Allergy Organization Journal · 2015
Typearticle
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsHealth Sciences Centre
FundersAllergopharmaMylanNovartis PharmaSanofi
KeywordsAnaphylaxisMedicineIntensive care medicineAllergyDiseaseEpidemiologyImmunologyPathology

Abstract

fetched live from OpenAlex

The World Allergy Organization (WAO) Guidelines for the assessment and management of anaphylaxis provide a unique global perspective on this increasingly common, potentially life-threatening disease. Recommendations made in the original WAO Anaphylaxis Guidelines remain clinically valid and relevant, and are a widely accessed and frequently cited resource. In this 2015 update of the evidence supporting recommendations in the Guidelines, new information based on anaphylaxis publications from January 2014 through mid- 2015 is summarized. Advances in epidemiology, diagnosis, and management in healthcare and community settings are highlighted. Additionally, new information about patient factors that increase the risk of severe and/or fatal anaphylaxis and patient co-factors that amplify anaphylactic episodes is presented and new information about anaphylaxis triggers and confirmation of triggers to facilitate specific trigger avoidance and immunomodulation is reviewed. The update includes tables summarizing important advances in anaphylaxis research.

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)0.013
metaresearch head score (Gemma)0.076
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 score0.014
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.076
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0140.011
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0040.002
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0100.004

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 head0.063
GPT teacher head0.329
Teacher spread0.266 · 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

Citations588
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueWorld Allergy Organization JournalSame topicFood Allergy and Anaphylaxis ResearchFrench-language works237,207