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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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Remote Sensing and LiDAR Applications
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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.

2,536 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.
2,536 works in the cohort · of 4,299,418page 35 of 51

Labels cover 3 of 2,536 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 2,536 of 2,536 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.

afffundaboutunlabeled
VALIDATION OF SPACEBORNE RADAR SURFACE WATER MAPPING WITH OPTICAL sUAS IMAGES
Julien Li-Chee-Ming, Kevin Murnaghan, Donald L. Sherman, Valentin Poncoș, Brian Brisco, Costas Armenakis
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· Environmental Science
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Galaxy: a new state of the art airborne lidar system
Daryl Hartsell, P. E. LaRocque, Jeffrey W. Tripp
2016· article· en· Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE· Environmental Science
machine prediction:candidate · noneconsensus · none
2
citations
afffundunlabeled
Preliminary design of an aerial cliff sampling system
Hughes La Vigne, Guillaume Charron, Julien Rachiele Tremblay, Ben Nyberg, Alexis Lussier Desbiens
2021· article· en· Environmental Science
machine prediction:candidate · noneconsensus · none
2
citations
afffundunlabeled
In Memorium: Thomas Hilker
Alexei Lyapustin, Nicholas C. Coops, Forrest G. Hall, Compton J. Tucker, P. J. Sellers, Lênio Soares Galvão +4 more
2016· article· en· Remote Sensing· Environmental Science
machine prediction:candidate · noneconsensus · none
2
citations
afffundunlabeled
SIMULATION-BASED DATA AUGMENTATION USING PHYSICAL PRIORS FOR NOISE FILTERING DEEP NEURAL NETWORK
M. Jameela, Luan Chen, Andrew Sit, Jaemin Yoo, C. Verheggen, Gunho Sohn
2020· 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· Environmental Science
machine prediction:candidate · noneconsensus · none
1
citations
afffundunlabeled
A PROCEDURE FOR THE REGISTRATION AND SEGMENTATION OF HETEROGENEOUS LIDAR DATA
M. Al-Durgham, Ayman Habib
2012· 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· Environmental Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Terrestrial Method for Airborne Lidar Quality Control and Assessment
Naif Muidh Alsubaie, Hameed Badawy, 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· Environmental Science
machine prediction:candidate · noneconsensus · none
1
citations

How this was built: Screen · Findings · About