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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.

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.

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 45 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.

affunlabeled
Subaru/HSC Goldrush catalog
Yuichi Harikane, Yoshiaki Ono, Masami Ouchi, Chengze Liu, Marcin Sawicki, Takatoshi Shibuya +13 more
2021· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
ASSESSMENT OF RADARSAT-2 HR STEREO DATA OVER CANADIAN NORTHERN AND ARCTIC STUDY SITES
Thierry Toutin, Khalid Omari, Enrique Blondel, Daniel Clavet, Carla Schmitt
2013· 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
0
citations
affaboutunlabeled
Preface: ISPRS Geospatial Week 2023
Naser El‐Sheimy, Alaa Abdelbary, Nashwa El-Bendary, Yahya Mohasseb
2023· article· en· ISPRS annals of the photogrammetry, remote sensing and spatial information sciences· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Comparative Analysis of UAVSAR Polarimetric Decompositions for Wetland Aboveground Biomass Mapping Using Machine Learning Models
Mohammadali Hemati, Masoud Mahdianpari, Hodjat Shiri, Fariba Mohammadimanesh
2025· 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
0
citations
affunlabeled
Preface: Workshop “Smart Forests – Forest ecosystem assessment and monitoring using Remote Sensing, Artificial Intelligence, and Robotics”
Xinlian Liang, Yunsheng Wang, Francesco Pirotti, Joanne C. White, Fabian Ewald Fassnacht, Maria Teresa Melis +5 more
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· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
afffundunlabeled
PREFACE: TECHNICAL COMMISSION III
J. Jiang, A. Shaker, H. Zhang
2021· article· en· ISPRS annals of the photogrammetry, remote sensing and spatial information sciences· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affvenueaboutunlabeled
Progrès dans l’application de la télédétection pour les besoins en matière d’information sur les forêts au Canada : leçons tirées d’une collaboration nationale d’intervenants universitaires, industriels et gouvernementaux
Nicholas C. Coops, Alexis Achim, Paul A. Arp, Christopher W. Bater, John P. Caspersen, Jean‐François Côté +17 more
2021· article· fr· The Forestry Chronicle· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Exploring State Space Models in LiDAR Point Cloud Segmentation
Dening Lu, Linlin Xu, Ruisheng Wang, Jonathan Li
2025· 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
0
citations

How this was built: Screen · Findings · About