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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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Time Series Analysis and Forecasting
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.

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.

560 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.
560 works in the cohort · of 4,299,418page 8 of 12

Labels cover 0 of 560 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 560 of 560 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affunlabeled
Contrastive Learning for Time Series on Dynamic Graphs
Yitian Zhang, Florence Regol, Antonios Valkanas, Mark Coates
2022· article· en· 2022 30th European Signal Processing Conference (EUSIPCO)· Computer Science
distilled prediction:candidate · metaepi_narrow+stsconsensus · none
1
citations
affno abstractunlabeled
UWaterlooMDS at the TREC 2019 Decision Track.
Mustafa Abualsaud, Fuat Can Beylunioğlu, Mark D. Smucker, P. Robert Duimering
2019· article· en· Text REtrieval Conference· Computer Science
distilled prediction:candidate · insufficient_payloadconsensus · insufficient_payload
1
citations
affno abstractunlabeled
Time Series Analysis Methods
Richard E. Thomson, William J. Emery
2024· book-chapter· en· Elsevier eBooks· Computer Science
distilled prediction:candidate · metaepi_narrow+insufficient_payloadconsensus · insufficient_payload
1
citations
affno abstractunlabeled
Fast Tractography Streamline Search
Etienne St‐Onge, Eleftherios Garyfallidis, D. Louis Collins
2021· book-chapter· en· Lecture notes in computer science· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communicationconsensus · none
1
citations
aboutno affunlabeled
Deep sea spy: a collaborative annotation tool
Marjolaine Matabos, Catherine Borremans, P. Bossard, Julie Tourolle, Jozée Sarrazin
2018· article· en· Instrumentation viewpoint· Computer Science
distilled prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Learning to predict trending queries
Chi‐Hoon Lee, Hengshuai Yao, Xu He, Su Han Chan, JieYang Chang, Farzin Maghoul
2014· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Christos Faloutsos speaks out
Marianne Winslett
2005· article· en· ACM SIGMOD Record· Computer Science
distilled prediction:candidate · insufficient_payloadconsensus · none
1
citations
affunlabeled
Extracting Situations with Uneasy Driving in NDS-Data
Tobias Karlsson, Magdalena Lindman, Jordanka Kovaceva, Bo Svanberg, Henrik Wiberg, Lotta Jakobsson
2014· article· en· SAE technical papers on CD-ROM/SAE technical paper series· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
1
citations
aboutno affno abstractunlabeled
Ensemble Prediction at the Canadian Meteorological Centre
G. Pellerin, L. Lefaivre, P. L. Houtekamer, Herschel L. Mitchell
2004· article· en· AGU Spring Meeting Abstracts· Computer Science
distilled prediction:candidate · noneconsensus · none
0
citations
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