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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
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.

1,725 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.
1,725 works in the cohort · of 4,299,418page 29 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
Preface
Kai Erikson
2014· other· en· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Working with Principles and Visions
Sharon Almerigi, Lucia Fanning, Robin Mahon, Patrick McConney
2013· book-chapter· en· MARE publication series· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Managing risk and vulnerability
Jacqueline Best
2014· book-chapter· en· Cambridge University Press eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
In Reply to Avalanche Triage
Lee B. Bogle, Jeff Boyd, Kyle McLaughlin
2010· article· en· Wilderness and Environmental Medicine· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s0197-2510(06)70470-3
2000· article· en· Time to knit· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affno abstractunlabeled
Canada - Disasters
2015· dataset· en· Foreign Law Guide· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Emergency Response Networks
Reda Alhajj, Jon Rokne
2018· book-chapter· en· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About