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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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Network Modeling Analysis in Health Informatics and Bioinformatics
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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.

affaffiliation
fundfunder
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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.

32 results · 1 filter active ·
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20132025
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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.
32 works in the cohort · of 4,299,418page 1 of 1

Labels cover 0 of 32 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 32 of 32 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.

affno abstractunlabeled
Mining clinical text for stroke prediction
Elham Sedghi, Jens Weber, Alex Thomo, Maximilian B. Bibok, Andrew M. Penn
2015· article· en· Network Modeling Analysis in Health Informatics and Bioinformatics· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
17
citations
afffundno abstractunlabeled
Using Twitter for diabetes community analysis
Krunal Dhiraj Patel, Kazi Zainab, Andrew Heppner, Gautam Srivastava, Vijay Mago
2020· article· en· Network Modeling Analysis in Health Informatics and Bioinformatics· Social Sciences
machine prediction:candidate · noneconsensus · none
14
citations
afffundno abstractunlabeled
SARS-CoV-2 transmission in university classes
William E. Ruth, Richard Lockhart
2022· article· en· Network Modeling Analysis in Health Informatics and Bioinformatics· Mathematics
machine prediction:candidate · noneconsensus · none
3
citations
afffundno abstractunlabeled
Are brain networks classifiable?
Keanelek Enns, Kazi Tabassum Ferdous, Sowmya Balasubramanian, Smita Ghosh, Venkatesh Srinivasan, Alex Thomo
2024· article· en· Network Modeling Analysis in Health Informatics and Bioinformatics· Neuroscience
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About