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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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Hemophilia Treatment and Research
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.

1,707 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.
1,707 works in the cohort · of 4,299,418page 15 of 35

Labels cover 2 of 1,707 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 1,707 of 1,707 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.

affvenueunlabeled
Acquired hemophilia A presenting post partum
Kristine Mytopher, Jill Dudebout, Robert Card, Barry Gilliland
2007· article· en· Canadian Medical Association Journal· Medicine
machine prediction:candidate · noneconsensus · none
11
citations
affaboutunlabeled
Outcome assessment and limitations
Pradeep Mathew Poonnoose, Shyamkumar N. Keshava, Sridhar Gibikote, Brian M. Feldman
2012· article· en· Haemophilia· Medicine
machine prediction:candidate · metaresearchconsensus · none
11
citations
fundno affRetractionunlabeled
Abstracts
Johannes Oldenburg, Margareth C. Ozelo, Robert Klamroth, Benoît Guillet, Angela Huth-Kuehne
2020· article· it· Haemophilia· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
10
citations
affunlabeled
Psychological interventions for people with hemophilia
F. Cassis, Francesca Emiliani, John Pasi, Laura Palareti, Alfonso Iorio
2012· article· en· Cochrane Database of Systematic Reviews· Medicine
machine prediction:candidate · noneconsensus · none
10
citations
affno abstractunlabeled
Inhibitor Economics
Jerome Teitel
2006· review· en· Seminars in Hematology· Medicine
machine prediction:candidate · noneconsensus · none
10
citations
venueno affunlabeled
Acquired Hemophilia A After SARS-CoV-2 Infection: A Case Report
Jennifer Nardella, Domenico Comitangelo, Renato Marino, Giuseppe Malcangi, Marco Damiano Barratta, Carlo Sabbà +1 more
2022· article· en· Journal of Medical Cases· Medicine
machine prediction:candidate · noneconsensus · none
10
citations

How this was built: Screen · Findings · About