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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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International Journal for Population Data Science
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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.

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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.

810 results · 1 filter active ·
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20172025
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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.
810 works in the cohort · of 4,299,418page 7 of 17

Labels cover 7 of 810 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 810 of 810 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affaboutunlabeled
Through the legal maze: An Act Respecting Research
Ted McDonald, Patricia MacKenzie, Krista Barry
2018· article· en· International Journal for Population Data Science· Medicine
distilled prediction:candidate · metaresearch+stsconsensus · none
0
citations
affaboutunlabeled
Lessons from the past: A window on the future
Alan Katz, Marni Brownell, Mark Smith
2018· article· en· International Journal for Population Data Science· Medicine
distilled prediction:candidate · metaresearchconsensus · none
0
citations
affaboutgemma · no categorygpt · no categorymodels split
Reporting on the establishment of a Privacy Preserving Record Linkage to Facilitate an Ongoing Crosswalk Between Research and Health Administrative Databases
Brendan Behan, Alana Sparks, Heena Cheema, Sibel Naska, Francis Jeanson, Shalane Basque +5 more
2024· article· en· International Journal for Population Data Science· Decision Sciences
distilled prediction:candidate · metaresearch+scholarly_communicationconsensus · metaresearch
0
citations
affaboutunlabeled
Administrative health data validity: Changes over 19 years
Jie Pan, Seungwon Lee, Cheligeer Cheligeer, Natalie Sapiro, Bing Li, Guosong Wu +3 more
2024· article· en· International Journal for Population Data Science· Economics, Econometrics and Finance
distilled prediction:candidate · scholarly_communicationconsensus · none
0
citations
aboutno affunlabeled
Comparing Methods for Missing Paternal Linkages in Administrative Data
Amani F. Hamad, Barret A. Monchka, Oleguer Plana‐Ripoll, Olawale F. Ayilara, Lisa M. Lix
2024· article· en· International Journal for Population Data Science· Social Sciences
distilled prediction:candidate · scholarly_communicationconsensus · none
0
citations
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