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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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COVID-19 and healthcare impacts
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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.

2,192 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.
2,192 works in the cohort · of 4,299,418page 38 of 44

Labels cover 8 of 2,192 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 2,192 of 2,192 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.

affunlabeled
In reply to Drs Magrini, Mazzola, Greco, Alongi, Buglione
Richard Simcock, Toms Vengaloor Thomas, Christopher Estes, Andrea Riccardo Filippi, Matthew S. Katz, Ian Pereira +1 more
2020· article· en· Clinical and Translational Radiation Oncology· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
103 ORTHOGERIATRIC SERVICES IN THE FACE OF COVID-19
N Davey, A McFeely, P Doyle, Aidan Stankard, S Coveney, N Alsubie +13 more
2021· article· en· Age and Ageing· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
venueaboutno affunlabeled
The singles' scene
John M. Tallon
2003· article· en· Canadian Medical Association Journal· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
Post-COVID primary care reboot?
Kimberly Wintemute, Guylène Thériault
2021· article· en· Canadian Family Physician· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
Reply by Authors
Avril Lusty, R. Christopher Doiron, Christopher M. Booth, Marlo Whitehead, D. Robert Siemens
2021· letter· en· The Journal of Urology· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Editorial Comment
Emmanuel O. Abara
2023· editorial· es· The Journal of Urology· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Pandemic and scientific events
Alexandru Grigorescu
2021· article· en· Oncolog-Hematolog ro· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
COVID-19 Lockdown: Not a One Size Fits All
Yasmina Gaber, Priscilla Matthews
2021· article· en· McMaster University Medical Journal· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations

How this was built: Screen · Findings · About