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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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Zenodo (CERN European Organization for Nuclear Research)
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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.

82,802 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.
82,802 works in the cohort · of 4,299,418page 15 of 1,657

Labels cover 111 of 82,802 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 82,802 of 82,802 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.

affunlabeled
Using R in Hydrology at EGU2018
Louise Slater, Claudia Vitolo, Shaun Harrigan, Tobias Gauster, Guillaume Thirel, Alexander Hurley
2018· article· en· Zenodo (CERN European Organization for Nuclear Research)· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
2
citations
affunlabeled
Gymnasium
2024· other· en· Zenodo (CERN European Organization for Nuclear Research)
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
opesci/devito: Devito-3.0.2
2017· other· en· Zenodo (CERN European Organization for Nuclear Research)
machine prediction:candidate · insufficient_payloadconsensus · none
2
citations
affunlabeled
Indicators of Global Climate Change 2022
2023· other· en· Zenodo (CERN European Organization for Nuclear Research)· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
CEDS_GBD-MAPS: Data Snapshot (2014 - 2015)
Erin E. McDuffie, Steven J. Smith, Patrick O’Rourke, Kushal Tibrewal, Chandra Venkataraman, Eloïse A. Marais +4 more
2020· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Decision Sciences
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
OpenKinect/libfreenect2:
2021· other· en· Zenodo (CERN European Organization for Nuclear Research)
machine prediction:candidate · insufficient_payloadconsensus · none
2
citations
affunlabeled
Ouranosinc/xclim: v0.39.0
2022· other· en· Zenodo (CERN European Organization for Nuclear Research)
machine prediction:candidate · insufficient_payloadconsensus · none
2
citations
affunlabeled
Dataset for the TDP-43 antibody screening study
Carl Laflamme
2023· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Sondage sur la capacité des services institutionnels de gestion des données de recherche, rapport INSIGHTS no2 Capacité des établissements au chapitre du personnel hautement qualifié, de l'infrastructure et des services
Alexandra Cooper, Lucia Costanzo, Dylanne Dearborn, Shahira Khair, Carol Perry, Andrea Szwajcer +1 more
2021· report· fr· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · metaresearchconsensus · none
2
citations
affunlabeled
PredictiveEcology/LandR-Manual: v1.0.3
2022· other· en· Zenodo (CERN European Organization for Nuclear Research)
machine prediction:candidate · insufficient_payloadconsensus · none
2
citations
affunlabeled
neurostuff/NiMARE: 0.0.12
2022· other· en· Zenodo (CERN European Organization for Nuclear Research)
machine prediction:candidate · insufficient_payloadconsensus · none
2
citations
affunlabeled
bids-specification
2023· other· en· Zenodo (CERN European Organization for Nuclear Research)· Arts and Humanities
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
napari: a multi-dimensional image viewer for Python
Nicholas Sofroniew, Talley J. Lambert, Grzegorz Bokota, Juan Nunez-Iglesias, Peter Sobolewski, Andrew Sweet +77 more
2025· other· Zenodo (CERN European Organization for Nuclear Research)
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
pytroll/pyresample: Version 1.26.0 Post 0
2022· other· en· Zenodo (CERN European Organization for Nuclear Research)
machine prediction:candidate · insufficient_payloadconsensus · none
2
citations
affunlabeled
D4.3 – IPSP Guidelines
2024· article· en· Zenodo (CERN European Organization for Nuclear Research)· Decision Sciences
machine prediction:candidate · scholarly_communicationconsensus · none
2
citations
affunlabeled
GIEMS-MethaneCentric v1.0
2024· dataset· en· Zenodo (CERN European Organization for Nuclear Research)
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
SunPy
2023· other· en· Zenodo (CERN European Organization for Nuclear Research)
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
tardis-sn/tardis: TARDIS v2023.08.13
2023· other· en· Zenodo (CERN European Organization for Nuclear Research)
machine prediction:candidate · insufficient_payloadconsensus · none
2
citations
affunlabeled
Pedagogical encounters in music
Cecilia Ferm Almqvist, Cathy Benedict, Panagiotis A. Kanellopoulos
2017· article· en· Zenodo (CERN European Organization for Nuclear Research)· Social Sciences
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Tractography Challenge ISMRM 2015 b=3000s/mm² Data.
Peter Neher, Jean‐Christophe Houde, Maxime Descoteaux, Klaus Maier‐Hein
2017· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Medicine
machine prediction:candidate · noneconsensus · none
2
citations

How this was built: Screen · Findings · About