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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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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.

affaffiliation
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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 21 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
Editor's Note
2011· article· en· Lincoln (University of Nebraska)· Materials Science
distilled prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Conclusion
2017· book-chapter· fr· OpenEdition (OpenEdition)· Materials Science
distilled prediction:candidate · metaepi_narrow+sts+scholarly_communication+research_integrity+insufficient_payloadconsensus · metaepi_narrow+sts+scholarly_communication+insufficient_payload
0
citations
afffundunlabeled
j-IR-vis: Vision model for Infrared spectroscopy embeddings
Rudra Sondhi, E. CHACKO, Rodrigo A. Vargas–Hernández
2025· article· ChemRxiv· Materials Science
distilled prediction:candidate · metaepi_narrow+scholarly_communication+insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
CHES 2021 Artifact Review
Douglas Stebila
2022· article· en· DOAJ (DOAJ: Directory of Open Access Journals)· Materials Science
distilled prediction:candidate · metaepi_narrow+scholarly_communication+open_science+insufficient_payloadconsensus · none
0
citations
affaboutunlabeled
10th International Symposium on Group IV, V, VI elements
Gregory S. Patience, Yanet Villasana, Maoline D. Houndedoke, M. Olga Guerrero‐Pérez
2024· article· en· Catalysis Today· Materials Science
distilled prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Nanaimo Free Press [Friday, April 14, 1899]
2019· other· en· VIURRSpace (Vancouver Island University)· Materials Science
distilled prediction:candidate · metaepi_narrow+insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
ISMRM Reproducible Research Study Group: Data for the paper "CG-SENSE revisited: Results from the first ISMRM reproducibility challenge"
Oliver Maier, Steven H. Baete, Alexander Fyrdahl, Kerstin Hammernik, Seb Harrevelt, Lars Kasper +8 more
2020· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Materials Science
distilled prediction:candidate · metaresearch+metaepi_narrow+sts+scholarly_communication+open_science+insufficient_payloadconsensus · metaresearch+open_science+insufficient_payload
0
citations
affunlabeled
CanRelIncs.tab
Michael Donnelly
2020· dataset· hu· Harvard Dataverse· Materials Science
distilled prediction:candidate · metaepi_narrow+scholarly_communication+open_science+insufficient_payloadconsensus · metaepi_narrow+insufficient_payload
0
citations
affno abstractunlabeled
IWSF & SHIFT 2022 Workshop Committee: ISSREW 2022
Workshop Chairs, Sigrid Eldh, Alf Larsson, Sweden Ericsson
2022· article· en· Materials Science
distilled prediction:candidate · metaepi_narrow+sts+insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Code and Data for "Routescore: Punching the Ticket to More Efficient Materials Development"
Martin Seifrid, Riley J. Hickman, Andrés Aguilar‐Granda, Cyrille Lavigne, Jenya Vestfrid, Tony Wu +3 more
2021· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Materials Science
distilled prediction:candidate · metaepi_narrow+sts+scholarly_communication+open_science+insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
THERMEC 2021
Mihail Ionescu, Christof Sommitsch, María Cecilia Poletti, Ernst Kozeschnik, T. Chandra
2021· book· en· Trans Tech Publications Ltd. eBooks· Materials Science
distilled prediction:candidate · metaepi_narrow+insufficient_payloadconsensus · insufficient_payload
0
citations

How this was built: Screen · Findings · About