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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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Disaster Management and Resilience
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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.

1,725 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.
1,725 works in the cohort · of 4,299,418page 31 of 35

Labels cover 2 of 1,725 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 1,725 of 1,725 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.

aboutno affunlabeled
Natural disasters : editors comment
Bridget Farham
2010· article· fr· CME: Your SA Journal of CPD· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Terror in Schools
Steve Holden
2006· article· en· Teacher: The National Education Magazine· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Pandemic Planning
Michelle Murti, Steve Reynolds
2016· book-chapter· en· IMPERIAL COLLEGE PRESS eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
[no title]
Issa J. Boullata
2013· article· World Literature Today· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
Resilient Leaders for Resilient Cities
Cheick Fousseni Diaby, Christophe Roux‐Dufort
2020· article· en· IOP Conference Series Earth and Environmental Science· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Findings from Follow-up Interviews
Liette Vasseur, Mary J. Thornbush, Steve Plante
2017· book-chapter· en· Springer briefs in geography· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
Global Fire Weather Indices - FFMC using default DC start-up
Megan McElhinny, Piyush Jain, Justin Beckers, Chelene Hanes, Mike Flannigan
2019· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Caught out in a Crisis
Stephen Beamon
2010· article· en· Rail professional· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
Flood hazard study North Vancouver
Thomas Lyle
2013· report· en· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
SOS! Canadian Disasters
Programs Branch
2006· article· en· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Sensation Avoiding
Sandy Thompson‐Hodgetts
2013· book-chapter· en· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Witness to a catastrophe
Simron Jit Singh
2015· article· en· The New Scientist· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Disaster Risk Management in China
David L. Olson, Desheng Wu
2010· book-chapter· en· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About