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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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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
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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 18 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
Subjective mapping
Michael Bowling, Dana Wilkinson, Ali Ghodsi
2006· article· en· National Conference on Artificial Intelligence· Engineering
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
DeReEs
Sahand Seifi, Afsaneh Rafighi, Oscar Meruvia-Pastor
2014· article· en· Engineering
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
An efficient binary corner detector
Parvaneh Saeedi, David Lowe, Peter Lawrence
2004· article· en· Engineering
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
THE PERFORMANCE ANALYSIS OF AN INDOOR MOBILE MAPPING SYSTEM WITH RGB-D SENSOR
Guang-Je Tsai, Kai‐Wei Chiang, Chao‐Hsien Chu, Y. L. Chen, Naser El‐Sheimy, Ayman Habib
2015· article· en· ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences· Engineering
machine prediction:candidate · noneconsensus · none
5
citations
afffundunlabeled
LIDAR-INERTIAL LOCALIZATION WITH GROUND CONSTRAINT IN A POINT CLOUD MAP
Mengchi Ai, I. Asl Sabbaghian Hokmabadi, Mohamed Elhabiby, M. Moussa, Abdelhalim Zekry, Ashraf A. Mohamed +1 more
2023· article· en· ISPRS annals of the photogrammetry, remote sensing and spatial information sciences· Engineering
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
IMPROVED REFERENCE KEY FRAME ALGORITHM
H. A. Mohamed, A. Moussa, Mohamed Elhabiby, Naser El‐Sheimy
2019· article· en· ISPRS annals of the photogrammetry, remote sensing and spatial information sciences· Engineering
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Omnidirectional Platform for Autonomous Mobile Industrial Robot
Badereddine Fares, Haïfa Souifi, Mohsen Ghribi, Yassine Bouslimani
2021· article· en· 2021 IEEE 3rd Eurasia Conference on IOT, Communication and Engineering (ECICE)· Engineering
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Real-time Mapping of Multi-Floor Buildings Using Elevators
Sahar Leisiazar, Mohammad Mahdavian, Edward J. Park, Mo Chen
2022· article· en· 2022 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)· Engineering
machine prediction:candidate · noneconsensus · none
5
citations
afffundno abstractunlabeled
A Mobile Robotic Platform for Generating Radiation Maps
Florentin von Frankenberg, Robin McDougall, Scott Nokleby, Ed Waller
2012· book-chapter· en· Lecture notes in computer science· Engineering
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
RGB-D Indoor Plane-based 3D-Modeling using Autonomous Robot
Navid Mostofi, A. Moussa, Mohamed Elhabiby, Naser El‐Sheimy
2014· article· en· ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences· Engineering
machine prediction:candidate · noneconsensus · none
4
citations
afffundaboutunlabeled
INVESTIGATING THE COMPLEMENTARY USE OF RADAR AND LIDAR FOR POSITIONING APPLICATIONS
Eslam Mounier, Emma Dawson, Mohamed Elhabiby, Michael J. Korenberg, Aboelmagd Noureldin
2023· article· en· ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences· Engineering
machine prediction:candidate · noneconsensus · none
4
citations
affno abstractunlabeled
An edge–fog architecture for distributed 3D reconstruction
V. F. Vidal, Leonardo de Mello Honório, Milena F. Pinto, Mário A. R. Dantas, Maria Aguiar, Miriam A. M. Capretz
2022· article· en· Future Generation Computer Systems· Engineering
machine prediction:candidate · noneconsensus · none
4
citations
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