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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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Landslides and related hazards
Retraction
Abstract
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Label status

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.

2,683 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.
2,683 works in the cohort · of 4,299,418page 23 of 54

Labels cover 0 of 2,683 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 2,683 of 2,683 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.

venueno affunlabeled
Three-dimensional levee and floodwall underseepage
Navid H. Jafari, Timothy D. Stark, A. Leopold, Scott M. Merry
2015· article· en· Canadian Geotechnical Journal· Environmental Science
machine prediction:candidate · noneconsensus · none
7
citations
affno abstractunlabeled
A numerical model of iceberg scour
Mohamed Sayed, G.W. Timco
2008· article· en· Cold Regions Science and Technology· Environmental Science
machine prediction:candidate · noneconsensus · none
7
citations
aboutno affunlabeled
Observation of Rockfall in the Thermal Infrared
Edward C. Wellman, Kirk W. Schafer, Greatness H. Ojum, J. J. Potter, Leonard D. Brown, Benjamin Meyer +2 more
2024· article· en· Rock Mechanics and Rock Engineering· Environmental Science
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
Mountain Geomorphology
Olav Slaymaker
2017· other· en· International Encyclopedia of Geography· Environmental Science
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
Hong Kong landslides
S. R. Hencher, Andrew W. Malone
2012· book-chapter· en· Cambridge University Press eBooks· Environmental Science
machine prediction:candidate · noneconsensus · none
6
citations
aboutno affunlabeled
WHICH OBS FOR WHICH AVALANCHE TYPE
Bruce Jamieson, Jürg Schweizer, Avisualanche Consulting
2010· article· en· DORA WSL (Swiss Federal Institute for Forest, Snow and Landscape Research)· Environmental Science
machine prediction:candidate · noneconsensus · none
6
citations
affvenueaboutunlabeled
Reply to the discussion by Olsen and Stuedlein on “Use of terrestrial laser scanning for the characterization of retrogressive landslides in sensitive clay and rotational landslides in river banks”Appears in Canadian Geotechnical Journal, <b>47</b>(10): 1164–1168.
Thierry Oppikofer, Michel Jaboyedoff, Denis Demers, Jacques Locat, Ariane Locat, Pascal Locat +2 more
2010· article· en· Canadian Geotechnical Journal· Environmental Science
machine prediction:candidate · noneconsensus · none
6
citations
afffundunlabeled
Sustainability Nexus AID: landslides and land subsidence
Mahdi Motagh, Shagun Garg, Francesca Cigna, Pietro Teatini, Alok Bhardwaj, Mir A. Matin +2 more
2024· article· en· Sustainability Nexus Forum· Environmental Science
machine prediction:candidate · noneconsensus · none
6
citations

How this was built: Screen · Findings · About