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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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Medical Imaging Techniques and Applications
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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
fundfunder
venuejournal
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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.

2,749 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.
2,749 works in the cohort · of 4,299,418page 49 of 55

Labels cover 4 of 2,749 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 2,749 of 2,749 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.

aboutno affunlabeled
SuperDARN data in netCDF format (2012-Nov)
Alex T. Chartier, Jordan R. Wiker
2022· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
SuperDARN data in netCDF format (2018-Aug)
Alex T. Chartier, Jordan R. Wiker
2022· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
SuperDARN data in netCDF format (2011-Jan)
Alex T. Chartier, Jordan R. Wiker
2022· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
SuperDARN data in netCDF format (2009-Apr)
Alex T. Chartier, Jordan R. Wiker
2022· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
SuperDARN data in netCDF format (1995-Jan)
Alex T. Chartier, Jordan R. Wiker
2022· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
SuperDARN data in netCDF format (2006-Apr)
Alex T. Chartier, Jordan R. Wiker
2022· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
SuperDARN data in netCDF format (2005-Jan)
Alex T. Chartier, Jordan R. Wiker
2022· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
SuperDARN Grid data in netCDF format (2020-May)
Alex T. Chartier, Jordan R. Wiker
2023· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
SuperDARN data in netCDF format (2021-Dec)
Alex T. Chartier, Jordan R. Wiker
2023· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Low Tesla MR Imaging for Spine with Hardware
S.N. Huh, Daniel J. Indelicato, Adam L. Holtzman, Roi Dagan, Jeong‐Yeol Park, Eric D. Brooks +2 more
2023· article· en· International Journal of Radiation Oncology*Biology*Physics· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
TargetAge targets (R data format)
Clare E. West, Mohd Anisul Karim, Maria J. Falaguera, Leo Speidel, Charlotte Green, Lisa Logie +10 more
2023· dataset· en· Figshare· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
dell latitude 5401 specs pdf
2024· other· fr· Zenodo (CERN European Organization for Nuclear Research)· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
Nuclear Medicine
Thomas J. Ruth
2003· other· en· digital Encyclopedia of Applied Physics· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
Bunsen Coefficient
Heinz Gamsjäger, John W. Lorimer, Pirketta Scharlin, David G. Shaw
2016· dataset· en· IUPAC Standards Online· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affvenueaboutunlabeled
We CANS do it: would a SANS on PC-CANS be worth it?
Maksymilian Dziura, Stuart R. Castillo, Dalini Maharaj, Stephen King, Robert Laxdal, O. Kester +1 more
2025· article· en· Canadian Journal of Physics· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Projekts Uzņēmuma SIA "Alberta" dibināšana
2015· dissertation· lv· E-resource repository of the University of Latvia (University of Latvia)· Medicine
machine prediction:candidate · noneconsensus · none
0
citations

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