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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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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
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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.

348 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.
348 works in the cohort · of 4,299,418page 1 of 7

Labels cover 0 of 348 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 348 of 348 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.

affunlabeled
In Vitro Bioactivity Assessment of Metallic Magnesium
Haydée Y. López, Dora A. Cortés‐Hernández, S. Escobedo, Diego Mantovani
2006· article· en· Key engineering materials· Materials Science
machine prediction:candidate · noneconsensus · none
50
citations
affno abstractunlabeled
On Alternative Representation of Forming Limits
Pei Dong Wu, Alex Graf, Mukesh Jain, S.R. MacEwen
2000· article· en· Key engineering materials· Computer Science
machine prediction:candidate · noneconsensus · none
9
citations

How this was built: Screen · Findings · About