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4,299,418 works, Canadian by any of four routes.

Every filter state is a URL; the URL is the query; the query is citable via /q/⟨hash⟩. The page, the API and the export parse the same parameters.

The current cohort, streamed from the database: every work column, the machine labels, the provisional scores, and the per-row validation status. Exports are capped at 100,000 rows. Mints a permanent /q/ link for this exact query. The same filters always produce the same link, whoever asks.

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Asthma and respiratory diseases
Retraction
Abstract
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Label status

Direct Codex and Gemma labels are unvalidated and sparse. Distilled predictions cover the full frame and are also unvalidated. Choose the evidence source explicitly; absence of a direct label is never a negative label.

affaffiliation
fundfunder
venuejournal
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

5,532 results · 1 filter active ·
Results by year
20002025
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Categories
Machine labels · sparse coverage
Evidence
Language
Type
Citations
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
5,532 works in the cohort · of 4,299,418page 90 of 111

Labels cover 27 of 5,532 works in this cohort. The rest are unlabeled, which is not a negative label: the label table is sparse today and grows as labeling rounds land.

Distilled predictions cover 5,532 of 5,532 works in this cohort. Predictions are machine_predicted_unvalidated. The Gemma side is a direct model label for every work (title-only); the Codex side is a distilled, calibrated classifier. Candidate is the union; consensus is the intersection.

afffundno abstractunlabeled
Response
Simon Couillard, D.J. Jackson, Ian Pavord, Michael E. Wechsler
2025· letter· en· CHEST Journal· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affvenueaboutunlabeled
Mild asthma in adults and adolescents
A. E. CRAWLEY, Kassy Strautman, Lindsey Zimmermann, Christine Ryan
2022· article· en· Canadian Family Physician· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
From the pages of AllergyWatch®
Stanley M. Fìneman, Gerald B. Lee, Bradley E. Chipps, John Oppenheimer
2020· article· en· Annals of Allergy Asthma & Immunology· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Cytokine cross-talk
James G. Martin
2004· article· en· Pediatric Pulmonology· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
fundno affno abstractunlabeled
Probiotics in United Airways Disease
Rashmi Ranjan Das
2011· letter· en· CHEST Journal· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Asthma control and action plans
Andrew Kouri, Louis‐Philippe Boulet, Alan Kaplan, Samir Gupta
2017· letter· en· European Respiratory Journal· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affvenueunlabeled
The authors' response
Padmaja Subbarao, Piush J. Mandhane, Malcolm R. Sears
2009· article· en· Canadian Medical Association Journal· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
EXTRAPOLATION OF ALLERGEN PC15
Donald W. Cockcroft, Beth E. Davis
2008· letter· en· Annals of Allergy Asthma & Immunology· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affvenueno abstractunlabeled
GOAL: What Have We Learned?
Timothy K. Vander Leek
2005· article· en· Allergy Asthma and Clinical Immunology· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Update on Asthma Medications
Nancy Runton
2002· review· en· The Nurse Practitioner· Medicine
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About