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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.

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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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Hormonal and reproductive studies
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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.

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

1,524 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
1,524 works in the cohort · of 4,299,418page 24 of 31

Labels cover 1 of 1,524 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 1,524 of 1,524 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.

venueno affunlabeled
Testosterone replacement and improved memory
Corey Lyon, Alicia Wong, Kristen DeSanto
2021· article· en· Canadian Family Physician· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Corrigendum to “Migration from RIA to LC-MS/MS for aldosterone determination: Implications for clinical practice and determination of plasma and urine reference range intervals in a cohort of healthy Belgian subjects” [Clin. Mass Spectrom. 9 (2018) 7–17]
Caroline M. Le Goff, Ana González‐Antuña, Stéphanie Peeters, Neus Fabregat-Cabello, J. Grace van der Gugten, Laurent Vroonen +3 more
2022· erratum· en· Journal of Mass Spectrometry and Advances in the Clinical Lab· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Screening for hypogonadism: real‐world considerations
Adrian Heald, Richard Jones, Adnan R. Khan, Gemma Donnahey, Paul Downie, Christopher J. Duff +1 more
2016· article· en· Trends in Urology & Men s Health· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
aboutno affunlabeled
The Global Epidemiology of Anabolic Steroid Use.
Dominic Sagoe, Helge Molde, Cecilie Schou Andreassen, Torbjørn Torsheim, Ståle Pallesen
2015· article· en· International Journal of Epidemiology· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Menopause and Sexual Function
Gillian Graves, Robert H. Lea, Gisèle Bourgeois‐Law
2001· article· en· Journal SOGC· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
True
Pascale Mauriège, A. Bèlanger, Fernand Labrie, Valérie Montminy, Yves Deshaies, JP Després +2 more
2000· article· en· International Journal of Obesity· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
1
citations
affno abstractunlabeled
Author Reply
Jordan D. Dimitrakoff, J. Curtis Nickel
2022· letter· en· Urology· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Advances in equine anti‐doping
Adam Cawley
2017· editorial· en· Drug Testing and Analysis· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
The Reply
Christel Renoux, Laurent Azoulay, Sophie Dell’Aniello, Oriana Hoi Yun Yu
2019· letter· en· The American Journal of Medicine· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
1
citations
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How this was built: Screen · Findings · About