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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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Atmospheric and Environmental Gas Dynamics
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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
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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.

5,307 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.
5,307 works in the cohort · of 4,299,418page 70 of 107

Labels cover 5 of 5,307 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 5,307 of 5,307 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.

affunlabeled
A Human World
2025· book-chapter· en· Cambridge University Press eBooks· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
CHAPTER 6 Uranium Policy in Nunavut
2022· book-chapter· en· University of Manitoba Press eBooks· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
blc20171016_03.txt
Robyn Fiori
2020· dataset· en· Harvard Dataverse· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Review of Sweeney et al.
Colm Sweeney
2020· peer-review· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
blc20160723_03.txt
Robyn Fiori
2020· dataset· en· Harvard Dataverse· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
blc20150313_03.txt
Robyn Fiori
2020· dataset· en· Harvard Dataverse· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(93)94653-g
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(96)83402-8
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affaboutunlabeled
Dissolved inorganic carbon, temperature, salinity and other variables collected from discrete sample and profile observations using CTD, bottle and other instruments from the METEOR in the Davis Strait, Gulf of Guinea and others from 1994-11-15 to 1994-12-19 (NCEI Accession 0113919)
H. THOMAS
2013· dataset· en· National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s0967-0653(97)83468-0
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/s0967-0653(97)84494-8
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/s0967-0653(98)81159-9
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
blc20150813_03.txt
Robyn Fiori
2020· dataset· en· Harvard Dataverse· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/s0967-0653(98)85713-x
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(94)93357-x
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(96)82390-8
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
blc20161114_03.txt
Robyn Fiori
2020· dataset· en· Harvard Dataverse· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Comment on acp-2022-155
Lu Shen, Ritesh Gautam, Mark Omara, Daniel Zavala‐Araiza, Joannes D. Maasakkers, Tia R. Scarpelli +10 more
2022· peer-review· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
The Canadian Climate
Jane Rule
2007· book-chapter· en· University of British Columbia Press eBooks· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
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