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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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Cystic Fibrosis Research Advances
Retraction
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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.

3,093 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
3,093 works in the cohort · of 4,299,418page 43 of 62

Labels cover 8 of 3,093 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 3,093 of 3,093 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.

affno abstractunlabeled
Bias in CFTR screening panels
Patrick R. Sosnay, Carlo Castellani, Christopher M. Penland, Johanna M. Rommens, Michelle Lewis, Karen S. Raraigh +2 more
2015· letter· en· Genetics in Medicine· Medicine
machine prediction:candidate · noneconsensus · none
4
citations
affvenueunlabeled
Exercise capacity of children with pediatric lung disease
Gerald S. Zavorsky, J R Kryder, S. V. Jacob, Allan L. Coates, Geoffrey M. Davis, Larry C. Lands
2009· article· en· Clinical and investigative medicine· Medicine
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
The Efficiency of Sputum Cell Counts in Cystic Fibrosis
Lata Jayaram, N. R. Labiris, Ann Efthimiadis, Helen Vlachos‐Mayer, Frederick E. Hargreave, Andreas Freitag
2007· article· en· Canadian Respiratory Journal· Medicine
machine prediction:candidate · noneconsensus · none
3
citations
aboutno affunlabeled
Pregnancy in women with cystic fibrosis
F. Edenborough
2002· article· en· Acta Obstetricia Et Gynecologica Scandinavica· Medicine
machine prediction:candidate · noneconsensus · none
3
citations
fundno affunlabeled
Cystic Fibrosis
Margarida D. Amaral, Karl Kunzelmann
2011· book· en· Methods in molecular biology· Medicine
machine prediction:candidate · noneconsensus · none
3
citations
afffundaboutunlabeled
Off-label use of inhaled tobramycin in Ontario, Canada
Mina Tadrous, Wayne Khuu, J. Michael Paterson, Muhammad Mamdani, David N. Juurlink, Tara Gomes
2016· letter· en· Thorax· Medicine
machine prediction:candidate · noneconsensus · none
3
citations
affunlabeled
Cystic Fibrosis: Modifier Genes
Aabida Saferali, Stuart E. Turvey, Andrew J. Sandford
2016· other· en· Encyclopedia of Life Sciences· Medicine
machine prediction:candidate · noneconsensus · none
3
citations
affno abstractunlabeled
Upper Airway Mucociliary Clearance is Impaired in Dyspneic COVID-19 Patients
Rogério Pezato, Andrea Goldwasser David, Alexandre Coelho Boggi, Bruna de Oliveira de Melo, Cláudia Maria Valete‐Rosalino, Athenea Pascual Rodríguez +2 more
2023· article· en· Indian Journal of Otolaryngology and Head & Neck Surgery· Medicine
machine prediction:candidate · noneconsensus · none
3
citations

How this was built: Screen · Findings · About