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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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3D Modeling in Geospatial Applications
Retraction
Abstract
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Study design
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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
venuejournal
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

346 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.
346 works in the cohort · of 4,299,418page 5 of 7

Labels cover 1 of 346 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 346 of 346 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.

affno abstractunlabeled
Geocomputation
2018· book-chapter· en· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Surficial mapping
I R Smith, R C Paulen, G W Hagedorn, M Pyne
2017· report· it· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Augmented Data
Reda Alhajj, Jon Rokne
2018· book-chapter· en· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s1526-4114(06)60136-4
Kathleen Wilson
2000· article· en· Time to knit· Engineering
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affunlabeled
Ruud van Empel : The Office
Mariona Fernández
2000· article· en· CV Photo· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
GEO-Bench: m-pv4ger-seg
Alexandre Lacoste, Niels Lehmann, Pau Rodríguez, Evan David Sherwin, Hannah Kerner, Björn Lütjens +11 more
2023· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s0967-0653(97)83763-5
2000· article· en· Time to knit· Engineering
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affno abstractunlabeled
Letter from the New Editors-in-Chief
Herbert Edelsbrunner, János Pach, Günter M. Ziegler
2010· letter· en· Discrete & Computational Geometry· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
fundno affunlabeled
3D Modeling for Multimodal Visualization of Medical Data
Hayssam Abd Alaziz Obeid, Rita Zrour, Bruno Mercier, Sébastien Horna, Carole Guillevin, Mathieu Naudin +1 more
2024· article· en· Computer-Aided Design and Applications· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Triangulated Terrains
Ling Liu, M. TAMER ÖZSU
2009· book-chapter· en· Encyclopedia of Database Systems· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
10.51847/ORv49btWEz
2000· article· en· Time to knit· Engineering
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
The Spatial Analyses of Data Fields
Richard E. Thomson, William J. Emery
2024· book-chapter· en· Elsevier eBooks· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
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How this was built: Screen · Findings · About