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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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Journal of materials research/Pratt's guide to venture capital sources
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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.

192 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.
192 works in the cohort · of 4,299,418page 2 of 4

Labels cover 0 of 192 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 192 of 192 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.

afffundno abstractunlabeled
Selective laser sintering of composite copper–tin powders
David C. Walker, W. F. Caley, Mathieu Brochu
2014· article· en· Journal of materials research/Pratt's guide to venture capital sources· Engineering
machine prediction:candidate · noneconsensus · none
23
citations
afffundno abstractunlabeled
Multiscale imaging and transport modeling for fuel cell electrodes
Jasna Janković, Shawn Zhang, Andreas Pütz, Madhu Sudan Saha, Darija Susac
2019· article· en· Journal of materials research/Pratt's guide to venture capital sources· Engineering
machine prediction:candidate · noneconsensus · none
22
citations
affno abstractunlabeled
Accelerating training of MLIPs through small-cell training
Jason Meziere, Yu Luo, Yi Xia, Laurent Karim Béland, Mark R. Daymond, Gus L. W. Hart
2023· article· en· Journal of materials research/Pratt's guide to venture capital sources· Materials Science
machine prediction:candidate · noneconsensus · none
17
citations
affno abstractunlabeled
Work function of doped zinc oxide films deposited by ALD
Péter Gordon, Goran Bačić, Gregory P. Lopinski, Seán T. Barry
2019· article· en· Journal of materials research/Pratt's guide to venture capital sources· Materials Science
machine prediction:candidate · noneconsensus · none
17
citations
affunlabeled
Deformation behaviour of ion-irradiated FeCr: A nanoindentation study
Kay Song, Hongbing Yu, Phani Karamched, Kenichiro Mizohata, David E.J. Armstrong, Felix Hofmann
2022· article· en· Journal of materials research/Pratt's guide to venture capital sources· Materials Science
machine prediction:candidate · noneconsensus · none
16
citations

How this was built: Screen · Findings · About