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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
fundfunder
venuejournal
aboutaboutness

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

96,016 results · 1 filter active ·
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20002025
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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.
96,016 works in the cohort · of 4,299,418page 11 of 1,921

Labels cover 321 of 96,016 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 96,016 of 96,016 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
Web Service Dataset
Eyhab Al‐Masri
2019· dataset· en· Figshare· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Urban Calgary GNSS Data
2024· dataset· en· Figshare· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
SMC Migration for Lamb et al. 2024
2024· dataset· en· Figshare· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Dataset 1.doc
Jin Wang, Jing Jiang, Yù Zhang, Yiwen Qian, Junfeng Zhang, Zhiliang Wang
2019· dataset· en· Figshare
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
1
citations
aboutno affunlabeled
Raw data VR Acceptance
Hanne Huygelier, Brenda Schraepen, Raymond van Ee, Vero Vanden Abeele, Céline R. Gillebert
2018· dataset· en· Figshare· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
1
citations
aboutno affunlabeled
Women and Teaching Profession
2023· article· en· Figshare· Social Sciences
machine prediction:candidate · noneconsensus · none
1
citations

How this was built: Screen · Findings · About