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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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Health, Environment, Cognitive Aging
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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.

1,205 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.
1,205 works in the cohort · of 4,299,418page 2 of 25

Labels cover 6 of 1,205 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 1,205 of 1,205 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.

afffundvenueunlabeled
Physical activity for brain health in older adults
Teresa Liu‐Ambrose, Cindy K. Barha, John R. Best
2018· review· en· Applied Physiology Nutrition and Metabolism· Environmental Science
machine prediction:candidate · noneconsensus · none
78
citations
affunlabeled
The Dementias Platform UK (DPUK) Data Portal
Sarah Bauermeister, Chris Orton, Simon Thompson, Roger A. Barker, Joshua Bauermeister, Yoav Ben‐Shlomo +59 more
2020· article· en· European Journal of Epidemiology· Environmental Science
machine prediction:candidate · noneconsensus · none
71
citations
afffundaboutunlabeled
Cohort Profile: The Saguenay Youth Study (SYS)
Zdenka Pausová, Tomáš Paus, Michał Abrahamowicz, Manon Bernard, Daniel Gaudet, Gabriel Leonard +5 more
2016· article· en· International Journal of Epidemiology· Environmental Science
machine prediction:candidate · noneconsensus · none
61
citations
afffundunlabeled
Developments in molecular epidemiology of aging
Sara Hägg, Daniel W. Belsky, Alan A. Cohen
2019· article· en· Emerging Topics in Life Sciences· Environmental Science
machine prediction:candidate · noneconsensus · none
61
citations
affunlabeled
EXPOsOMICS: final policy workshop and stakeholder consultation
Michelle C. Turner, Paolo Vineis, Eduardo Seleiro, Michaela Dijmarescu, David M. Balshaw, Roberto Bertollini +17 more
2018· article· en· BMC Public Health· Environmental Science
machine prediction:candidate · noneconsensus · none
49
citations
affunlabeled
Position Statement on Population Data Science:
Kim McGrail, Kerina Jones, Ashley Akbari, Tellen D. Bennett, Andy Boyd, Fabrizio Carinci +18 more
2018· article· en· International Journal for Population Data Science· Environmental Science
machine prediction:candidate · noneconsensus · none
47
citations
affno abstractunlabeled
Over-celling fetal microbial exposure
Katherine M. Kennedy, Christian J. Bellissimo, Jessica A. Breznik, Jon Barrett, Thorsten Braun, Frederic D. Bushman +12 more
2021· letter· en· Cell· Environmental Science
machine prediction:candidate · noneconsensus · none
43
citations
afffundaboutunlabeled
A method for generating synthetic longitudinal health data
Lucy Mosquera, Khaled El Emam, Lei Ding, Vishal Sharma, Xue Hua Zhang, Samer El Kababji +6 more
2023· article· en· BMC Medical Research Methodology· Environmental Science
machine prediction:candidate · noneconsensus · none
40
citations

How this was built: Screen · Findings · About