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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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Tactile and Sensory Interactions
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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.

1,524 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.
1,524 works in the cohort · of 4,299,418page 16 of 31

Labels cover 1 of 1,524 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 1,524 of 1,524 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.

afffundunlabeled
Your left hand can do it too!
Michelle Annett, Walter F. Bischof
2013· article· en· Neuroscience
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
A Hardware Based Braille Note Taker
Xuan Zhang, César Ortega-Sánchez, Iain Murray
2007· article· en· Neuroscience
machine prediction:candidate · noneconsensus · none
7
citations
affno abstractunlabeled
Direct Manipulation Interfaces
University Research Chair
2009· book-chapter· en· Encyclopedia of Database Systems· Neuroscience
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Demonstrating HapticBots
Ryo Suzuki, Eyal Ofek, Mike Sinclair, Daniel Leithinger, Mar González-Franco
2021· article· en· Neuroscience
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Distance sonification in image‐guided neurosurgery
Joseph Plazak, Simon Drouin, D. Louis Collins, Marta Kersten‐Oertel
2017· article· en· Healthcare Technology Letters· Neuroscience
machine prediction:candidate · noneconsensus · none
6
citations
affno abstractunlabeled
Development of a haptic video chat system
Longyu Zhang, Jamal Saboune, Abdulmotaleb El Saddik
2014· article· en· Multimedia Tools and Applications· Neuroscience
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Morphing in periodic tactile signals
Karon E. MacLean, Mario Enriquez, Tian Kuay Lim
2009· article· en· Neuroscience
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Visual Context and the Control of Movements through Video Display
Carole Ferrel, Jean-Pierre Orliaguet, Daniel Leifflen, Chantal Bard, Michelle Fleury
2001· article· en· Human Factors The Journal of the Human Factors and Ergonomics Society· Neuroscience
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Ergonomics of Tactile and Haptic Interactions
Jim Carter, B.F. van Jan
2006· article· en· Proceedings of the Human Factors and Ergonomics Society Annual Meeting· Neuroscience
machine prediction:candidate · noneconsensus · none
6
citations

How this was built: Screen · Findings · About