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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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Machine Learning in Materials Science
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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.

1,108 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.
1,108 works in the cohort · of 4,299,418page 16 of 23

Labels cover 4 of 1,108 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 1,108 of 1,108 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

aboutno affunlabeled
Traverser les frontières géographiques et littéraires
2019· article· it· Dialnet (Universidad de la Rioja)· Materials Science
distilled prediction:candidate · metaepi_narrow+scholarly_communication+insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Div_effects_Sp_level
Jon Urgoiti
2023· dataset· en· Figshare· Materials Science
distilled prediction:candidate · metaepi_narrow+insufficient_payloadconsensus · insufficient_payload
0
citations
afffundunlabeled
Local invertibility and sensitivity of atomic structure-feature mappings
Sergey N. Pozdnyakov, Liwei Zhang, Christoph Ortner, Gábor Cśanyi, Michele Ceriotti
2021· preprint· en· Open Research Europe· Materials Science
distilled prediction:candidate · metaepi_narrow+scholarly_communication+open_science+insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Interpretation of Rate Parameters
B. W. Wojciechowski, Nigel Rice
2003· book-chapter· en· Elsevier eBooks· Materials Science
distilled prediction:candidate · metaepi_narrow+insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Future Directions and Conclusions
Jimmy Lin, Rodrigo Nogueira, Andrew Yates
2022· book-chapter· en· Synthesis lectures on human language technologies· Materials Science
distilled prediction:candidate · metaepi_narrow+sts+insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Trend 1994 - 2011. Statistics Canada. CANSIM: Construction - Machinery and Equipment | Country: Canada | Table: Capital and repair expenditures, by sector and province | Variable: Aboriginal public administration (x 1,000,000), Capital and repair expenditures | Units: $CAD, 1994-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-034.
2015· other· en· Data Planet· Materials Science
distilled prediction:candidate · metaepi_narrow+insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Pelonaia corrugata Goodsir & Forbes 1841
2011· article· en· Zenodo (CERN European Organization for Nuclear Research)· Materials Science
distilled prediction:candidate · sts+insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
Catalyse
Muriel Gargaud, Ricardo Amils, José Cernicharo Quintanilla, William M. Irvine, Daniele L. Pinti, Michel Viso
2011· book-chapter· en· Encyclopedia of Astrobiology· Materials Science
distilled prediction:candidate · metaepi_narrow+insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Issue Information ‐ Table of Contents
2020· paratext· en· Glia· Materials Science
distilled prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
fundno affunlabeled
Robustness of kinetic screening against matter coupling
Guillermo Lara, Miguel Bezares, Marco Crisostomi, Enrico Barausse
2022· preprint· en· arXiv (Cornell University)· Materials Science
distilled prediction:candidate · metaepi_narrow+insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Towards Accurate Thermodynamics from Random Energy Sampling
Thomas Schüler, Maylise Nastar, Kangming Li, Chu‐Chun Fu
2023· preprint· en· SSRN Electronic Journal· Materials Science
distilled prediction:candidate · metaepi_narrow+scholarly_communication+research_integrityconsensus · none
0
citations
fundno affunlabeled
Contents list
2023· article· en· Chemical Communications· Materials Science
distilled prediction:candidate · insufficient_payloadconsensus · none
0
citations
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