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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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Climate Change Communication and Perception
Retraction
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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.

1,461 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.
1,461 works in the cohort · of 4,299,418page 29 of 30

Labels cover 27 of 1,461 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 1,461 of 1,461 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 affno abstractunlabeled
Sunlight on Snow
Nate Pritts
2016· article· en· The Trumpeter· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Introduction
Philippe D. Tortell
2020· book-chapter· en· Open Book Publishers· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Professional Ethics for Climate Scientists
Kent A. Peacock, Michael Mann
2014· article· en· AGU Fall Meeting Abstracts· Social Sciences
machine prediction:candidate · research_integrityconsensus · none
0
citations
affno abstractunlabeled
Reviews
Emily Gilbert
2001· article· en· Journal of Historical Geography· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
El reto de afrontar la crisis climática
Luis Bueno Ochoa, Enrique González Romero
2021· book-chapter· es· Cambridge University Press eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
fundno affno abstractunlabeled
Using Narrative to Explain Uncertainty in Climate Change
Grace Freeman, Alain N. Rousseau, Michelle Brunton, Stephanie Miller, Laura Kate Corlew
2025· preprint· Research Square· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
The day I should have died
Dan Swanson
2017· article· en· The New Scientist· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
Book reviews
Cooper H. Langford
2006· article· en· Science and Public Policy· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations

How this was built: Screen · Findings · About