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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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Data Quality and Management
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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.

867 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.
867 works in the cohort · of 4,299,418page 4 of 18

Labels cover 10 of 867 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 867 of 867 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.

affno abstractunlabeled
Dependency Discovery in Data Quality
Daniele Barone, Fabio Stella, Carlo Batini
2010· book-chapter· en· Notes on numerical fluid mechanics and multidisciplinary design· Decision Sciences
machine prediction:candidate · noneconsensus · none
18
citations
fundno affgemma · open_science+stsgpt · scholarly_communication+open_sciencemodels split
The Social Dynamics of Open Data
François Van Schalkwyk, Stefaan Verhulst, Gustavo Magalhães, Juan Pane, Johanna Walker
2017· book· en· African Minds eBooks· Decision Sciences
machine prediction:candidate · sts+open_scienceconsensus · none
17
citations
affunlabeled
Thank You to Our 2019 Peer Reviewers
Harihar Rajaram, Suzana J. Camargo, Rebecca Carey, Rose M. Corey, A. J. Dombard, Kathleen Donohue +21 more
2020· article· en· Geophysical Research Letters· Decision Sciences
machine prediction:candidate · metaresearchconsensus · none
17
citations
fundvenueno affgemma · open_sciencegpt · open_sciencemodels split
User Centred Methods for Measuring the Value of Open Data
Mark S. Frank, Johanna Walker
2016· article· en· The Journal of Community Informatics· Decision Sciences
machine prediction:candidate · metaresearch+open_scienceconsensus · none
17
citations
affno abstractunlabeled
Data Preprocessing
Christo El Morr, Manar Jammal, Hossam Ali‐Hassan, Walid El-Hallak
2022· book-chapter· en· International series in management science/operations research/International series in operations research & management science· Decision Sciences
machine prediction:candidate · noneconsensus · none
16
citations
affno abstractunlabeled
Data Profiling
Ziawasch Abedjan, Lukasz Golab, Felix Naumann, Thorsten Papenbrock
2018· article· en· Synthesis lectures on data management· Decision Sciences
machine prediction:candidate · noneconsensus · none
16
citations
affunlabeled
Effective Explanations for Entity Resolution Models
Tommaso Teofili, Donatella Firmani, Nick Koudas, Vincenzo Martello, Paolo Merialdo, Divesh Srivastava
2022· article· en· 2022 IEEE 38th International Conference on Data Engineering (ICDE)· Decision Sciences
machine prediction:candidate · noneconsensus · none
16
citations
affunlabeled
Ember
Sahaana Suri, Ihab F. Ilyas, Christopher Ré, Theodoros Rekatsinas
2021· article· en· Proceedings of the VLDB Endowment· Decision Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
15
citations
affaboutunlabeled
Linking 2006 Census and hospital data in Canada.
Michelle Rotermann, Claudia Sanmartin, Richard Trudeau, Hélène St-Jean
2015· article· en· PubMed· Decision Sciences
machine prediction:candidate · noneconsensus · none
15
citations
aboutno affunlabeled
Concordia University at the TREC 2007 QA Track.
Leila Kosseim, Alex Joseph Beaudoin, Abolfazl Keighobadi Lamjiri, Majid Razmara
2006· article· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
14
citations
affunlabeled
Dependable Data Repairing with Fixing Rules
Jiannan Wang, Nan Tang
2017· article· en· Journal of Data and Information Quality· Decision Sciences
machine prediction:candidate · noneconsensus · none
14
citations
aboutno affunlabeled
Data Management and Data Administration
Peter Aiken, Mark L. Gillenson, Xihui Zhang, David Rafner
2011· article· en· Journal of Database Management· Decision Sciences
machine prediction:candidate · noneconsensus · none
13
citations
affno abstractunlabeled
What Are Data?
Kärin Olson
2021· article· en· Qualitative Health Research· Decision Sciences
machine prediction:candidate · metaresearch+stsconsensus · none
13
citations
affno abstractunlabeled
Name2Vec: Personal Names Embeddings
Jeremy Foxcroft, Adrian d’Alessandro, Luiza Antonie
2019· book-chapter· en· Lecture notes in computer science· Decision Sciences
machine prediction:candidate · noneconsensus · none
13
citations
affno abstractunlabeled
Big Data Quality: A Data Quality Profiling Model
Ikbal Taleb, Mohamed Adel Serhani, Rachida Dssouli
2019· book-chapter· en· Lecture notes in computer science· Decision Sciences
machine prediction:candidate · noneconsensus · none
13
citations
affunlabeled
Editorial
Christian Bizer, Luna Dong, Ihab F. Ilyas, María-Esther Vidal
2016· editorial· en· Journal of Data and Information Quality· Decision Sciences
machine prediction:candidate · noneconsensus · none
12
citations
affunlabeled
Data linking over RDF knowledge graphs: A survey
Ali Assi, Hamid Mcheick, Wajdi Dhifli
2020· article· en· Concurrency and Computation Practice and Experience· Decision Sciences
machine prediction:candidate · noneconsensus · none
12
citations

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