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Record W2131291377 · doi:10.1186/s13223-015-0072-2

Insights and advances in chronic urticaria: a Canadian perspective

2015· article· en· W2131291377 on OpenAlexaffvenueabout
Gordon Sussman, Jacques Hébert, Wayne Gulliver, Charles Lynde, Susan Waserman, Amin Kanani, Moshe Ben‐Shoshan, Spencer Horemans, Carly C. Barron, Stephen Betschel, William H. Yang, Jan Dutz, Neil H. Shear, Gina Lacuesta, Peter Vadas, Kenneth Kobayashi, Hermenio Lima, F. Estelle R. Simons

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2015
Typearticle
Languageen
FieldMedicine
TopicUrticaria and Related Conditions
Canadian institutionsUniversity of OttawaMcGill UniversityUniversity of ManitobaKelowna General HospitalUniversity of British ColumbiaUniversity of British Columbia, Okanagan CampusMemorial University of NewfoundlandUniversité LavalMcMaster UniversityDalhousie UniversityUniversity of Toronto
Fundersnot available
KeywordsChronic urticariaOmalizumabMedicineIntensive care medicineChronic diseasePerspective (graphical)TerminologyDermatologyDiseaseQuality of life (healthcare)ImmunologyPathologyImmunoglobulin EComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

In the past few years there have been significant advances which have changed the face of chronic urticaria. In this review, we aim to update physicians about clinically relevant advances in the classification, diagnosis and management of chronic urticaria that have occurred in recent years. These include clarification of the terminology used to describe and classify urticaria. We also detail the development and validation of instruments to assess urticaria and understand the impairment on quality-of-life and the morbidity caused by this disease. Additionally, the approach to management of chronic urticaria now focuses on evidence-based use of non-impairing, non-sedating H1-antihistamines given initially in standard doses and if this is not effective, in up to 4-fold doses. For urticaria refractory to H1-antihistamines, omalizumab treatment has emerged as an effective, safe option.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.856
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.316
Teacher spread0.299 · 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 designTheoretical or conceptual
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

Citations51
Published2015
Admission routes3
Has abstractyes

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