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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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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.

946 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.
946 works in the cohort · of 4,299,418page 16 of 19

Labels cover 0 of 946 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 946 of 946 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

afffundunlabeled
SpeeDB: fast structural protein searches
David Robillard, Phelelani Thokozani Mpangase, Scott Hazelhurst, Frank Dehne
2015· article· en· Bioinformatics· Biochemistry, Genetics and Molecular Biology
distilled prediction:candidate · noneconsensus · none
6
citations
affunlabeled
SUBSTRA: Supervised Bayesian Patient Stratification
Sahand Khakabimamaghani, Yogeshwar Kelkar, Bruno M. Grande, Ryan D. Morin, Martin Ester, Daniel Ziemek
2019· article· en· Bioinformatics· Computer Science
distilled prediction:candidate · insufficient_payloadconsensus · none
6
citations
afffundunlabeled
BATL: Bayesian annotations for targeted lipidomics
Justin G. Chitpin, Anuradha Surendra, Thao Nguyen-Tran, Graeme Taylor, Hongbin Xu, Irina Alecu +8 more
2021· article· en· Bioinformatics· Biochemistry, Genetics and Molecular Biology
distilled prediction:candidate · noneconsensus · none
6
citations
affunlabeled
PEtab.jl: advancing the efficiency and utility of dynamic modelling
Sebastian Persson, Fabian Fröhlich, Stephan Grein, Torkel E. Loman, Damiano Ognissanti, Viktor Hasselgren +2 more
2025· article· en· Bioinformatics· Biochemistry, Genetics and Molecular Biology
distilled prediction:candidate · noneconsensus · none
5
citations
afffundunlabeled
NGS++: a library for rapid prototyping of epigenomics software tools
Alexei Nordell Markovits, Charles Joly Beauparlant, Dominique Toupin, Shengrui Wang, Arnaud Droit, Nicolas Gévry
2013· article· en· Bioinformatics· Biochemistry, Genetics and Molecular Biology
distilled prediction:candidate · noneconsensus · none
5
citations
affunlabeled
SBILib: a handle for protein modeling and engineering
Patrick Gohl, Jaume Bonet, Oriol Fornés, Joan Planas-Iglesias, Narcís Fernández‐Fuentes, Baldo Oliva
2023· article· en· Bioinformatics· Biochemistry, Genetics and Molecular Biology
distilled prediction:candidate · noneconsensus · none
5
citations

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