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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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Robotics and Sensor-Based Localization
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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.

1,640 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.
1,640 works in the cohort · of 4,299,418page 2 of 33

Labels cover 0 of 1,640 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 1,640 of 1,640 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
Multi-robot collaborative dense scene reconstruction
Siyan Dong, Kai Xu, Qiang Zhou, Andrea Tagliasacchi, Shiqing Xin, Matthias Nießner +1 more
2019· article· en· ACM Transactions on Graphics· Engineering
machine prediction:candidate · noneconsensus · none
109
citations
affunlabeled
Active object recognition
D. Wilkes, John K. Tsotsos
2003· article· en· Engineering
machine prediction:candidate · noneconsensus · none
103
citations
afffundaboutunlabeled
Review of Navigation Methods for UAV-Based Parcel Delivery
Didula Dissanayaka, Thumeera R. Wanasinghe, Oscar De Silva, Awantha Jayasiri, George K. I. Mann
2023· article· en· IEEE Transactions on Automation Science and Engineering· Engineering
machine prediction:candidate · noneconsensus · none
87
citations
affunlabeled
Multiscale 3D navigation
James McCrae, Igor Mordatch, Michael Glueck, Azam Khan
2009· article· en· Engineering
machine prediction:candidate · noneconsensus · none
81
citations
afffundunlabeled
Quality-driven poisson-guided autoscanning
Shihao Wu, Wei Sun, Pinxin Long, Hui Huang, Daniel Cohen‐Or, Minglun Gong +2 more
2014· article· en· ACM Transactions on Graphics· Engineering
machine prediction:candidate · noneconsensus · none
78
citations
fundno affunlabeled
Tracking a Depth Camera: Parameter Exploration for Fast ICP
François Pomerleau, Stéphane Magnenat, Francis Colas, Ming Liu, Roland Siegwart
2011· article· en· Repository for Publications and Research Data (ETH Zurich)· Engineering
machine prediction:candidate · noneconsensus · none
78
citations
affunlabeled
Super Generalized 4PCS for 3D Registration
Mustafa A. Mohamad, Mirza Tahir Ahmed, David Rappaport, Michael Greenspan
2015· article· en· Engineering
machine prediction:candidate · noneconsensus · none
74
citations
affunlabeled
Vision Based Modeling and Localization for Planetary Exploration Rovers
Stephen Se, Ho-Kong Ng, Piotr Jasiobedzki, Tai-Jing Moyung
2004· article· en· 55th International Astronautical Congress of the International Astronautical Federation, the International Academy of Astronautics, and the International Institute of Space Law· Engineering
machine prediction:candidate · noneconsensus · none
72
citations

How this was built: Screen · Findings · About