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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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Methane Hydrates and Related Phenomena
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.

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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.

3,528 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.
3,528 works in the cohort · of 4,299,418page 56 of 71

Labels cover 3 of 3,528 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 3,528 of 3,528 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
10.1016/0967-0653(94)91838-4
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)92948-3
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
Data for EMSL Project 50463 from November 2019
Adrian Tsang, Ronald P. de Vries, Miia Mäkelä, Mikael Andersen
2019· dataset· en· OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Data for EMSL Project 49375 from March 2020
John C. Linehan, Gregory K. Schenter, Wendy J. Shaw, Edo Apra, Garry W. Buchko, Bojana Ginovska +27 more
2020· article· en· OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(94)92256-x
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)83140-7
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)81275-0
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
Data for EMSL Project 51072 from January 2021
Adrian Tsang, Ronald P. de Vries, Miia Mäkelä
2021· dataset· en· OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Data for EMSL Project 51065 from July 2020
Laura Hug
2020· dataset· en· OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s0967-0653(98)85730-x
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/s0967-0653(95)97885-2
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(93)90198-g
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)84306-2
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(95)99094-8
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
Data for EMSL Project 51615 from June 2021
Irina Novikova, Walid A. Houry, Jeffrey Lynham, Marim Barghash, Mark Mabanglo, Thiago Vargas Seraphim +1 more
2021· dataset· en· OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(93)91603-a
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Timeseries of Arctic-Boreal Lake Area Derived from CubeSat Imagery, 2017
Sarah Cooley, L. C. Smith, Jonathan C. Ryan, L. H. Pitcher, Tamlin M. Pavelsky
2019· article· en· Oak Ridge National Laboratory Distributed Active Archive Center for Biogeochemical Dynamics· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s0967-0653(97)87090-1
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)84550-4
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)91921-6
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(93)94806-a
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(95)90791-v
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
Data for EMSL Project 51644 from January 2021
Irina Novikova, Harry Scott, N.C.J. Strynadka, Franco Li
2021· dataset· en· OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Data for EMSL Project 50463 from November 2019
Adrian Tsang, Ronald P. de Vries, Miia Mäkelä, Mikael Andersen
2019· dataset· en· OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Data for EMSL Project 51305 from September 2020
Theo Humphreys, Calvin K. Yip, John E. Burke, Udit Dalwadi, Manoj Kumar Rathinaswamy
2020· dataset· en· OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(93)92978-s
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
Data for EMSL Project 51615 from September 2022
Irina Novikova, Walid A. Houry, Jeffrey Lynham, Marim Barghash, Mark Mabanglo, Thiago Vargas Seraphim +1 more
2022· dataset· en· OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s0967-0653(97)82061-3
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)91199-1
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations

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