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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
Evidence
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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 39 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
Comment on essd-2021-281
2022· peer-review· en· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Occurrence Download
2023· dataset· en· Global Biodiversity Information Facility· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
01 HumanPhotopicLuminaSobel_thr0.15.png
Amanda Melin
2016· dataset· it· Harvard Dataverse· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Occurrence Download
2024· dataset· en· Global Biodiversity Information Facility· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
Suragina copelandi Muller 2024, sp. nov.
2024· article· fr· Zenodo (CERN European Organization for Nuclear Research)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
2014 OLC Lidar DEM: Colville, WA
Mineral Industries
2017· article· sw· downloadable data· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
Saskatoon By
2016· article· en· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Flux Sites Revisited: New Insights From a 3D-LiDAR Survey
Natascha Kljun, L. Chasmer, C. Hopkinson, Alan Barr, T. A. Black, J. H. McCaughey
2009· article· en· Cronfa (Swansea University)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Occurrence Download
2025· dataset· Global Biodiversity Information Facility· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
LIDAR Surveys for Road Design in Thailand
Chanchai Techashongs, Lek Chudasuta, Phisan Santitamnont, R. Simard, Pierre Bélanger
2004· article· en· Defense Technical Information Center (DTIC)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s0967-0653(97)89077-1
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Occurrence Download
2023· dataset· en· Global Biodiversity Information Facility· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Occurrence Download
2022· dataset· en· Global Biodiversity Information Facility· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
Polarimetric active imaging in dense fog
Robert Bernier, Xiaoying Cao, Grégoire Tremblay, G. Roy
2015· article· en· Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Magnetotelluric Transfer Functions
2017· other· en· NSF Seismological Facility for the Advancement of Geoscience (SAGE)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Occurrence Download
2023· dataset· en· Global Biodiversity Information Facility· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
venueno affno abstractunlabeled
Full Issue in PDF / Numéro complet enform PDF
2010· article· fr· Canadian Journal of Remote Sensing· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations

How this was built: Screen · Findings · About