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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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Hearing Loss and Rehabilitation
Retraction
Abstract
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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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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.

2,389 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.
2,389 works in the cohort · of 4,299,418page 41 of 48

Labels cover 3 of 2,389 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 2,389 of 2,389 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.

venueno affno abstractunlabeled
10.1145/3772318.3808914
AI Generated
2000· article· en· Time to knit· Neuroscience
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affunlabeled
10.51847/FVnellv1PU
2000· article· en· Time to knit· Neuroscience
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Adaptive wave field synthesis
Philippe-Aubert Gauthier
2008· article· en· The Journal of the Acoustical Society of America· Neuroscience
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Script.docx
2021· article· en· Figshare· Neuroscience
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
First Person
King Hei Chung
2014· article· en· The Hearing Journal· Neuroscience
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
Out of the Blue
Philippa Ovenden
2023· article· en· Music Theory Online· Neuroscience
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
The influence of music therapy in cochlear implant users
2017· dissertation· pt· Digital Library of Theses and Dissertations of the University of São Paulo (Universidade de São Paulo)· Neuroscience
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
relief des etats-unis pdf
2024· other· fr· Zenodo (CERN European Organization for Nuclear Research)· Neuroscience
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Studying Japanese electroacoustic musc : a view from Paris
マルク バティエ, みか子 水野, Marc Battier, Mikako Mizuno
2017· article· en· Institutional Repositories DataBase (IRDB)· Neuroscience
machine prediction:candidate · noneconsensus · none
0
citations
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