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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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Big Data and Business Intelligence
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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.

1,633 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.
1,633 works in the cohort · of 4,299,418page 20 of 33

Labels cover 10 of 1,633 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 1,633 of 1,633 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.

affaboutunlabeled
The Supply Chain Collaboration Online Research Simulator
Kewal Dhariwal, Peter Carr
2004· article· en· Proceedings of the International Conference on Networked Learning· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
NSERC business intelligence network: selected topics
Renée J. Miller, Frank Wm. Tompa, Sheila A. McIlraith, Jacob Slonim, Eric Yu
2011· article· en· Conference of the Centre for Advanced Studies on Collaborative Research· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Applied (Active Measures) Counterintelligence
John Ardis
2021· article· en· The Journal of Intelligence Conflict and Warfare· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
The Evidentiary Value of Big Data Analysis
Marco Pollanen, Bruce Cater
2017· article· en· IAFOR Journal of Politics Economics & Law· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
fundno affunlabeled
Research, and honesty
Arthur Charpentier
2013· article· en· OpenEdition (OpenEdition)· Business, Management and Accounting
machine prediction:candidate · research_integrityconsensus · none
0
citations
venueno affunlabeled
Computer Auditing: The way forward
Tawei Wang Tawei Wang, Shi-Ming Huang Tawei Wang
2019· article· en· International Journal of Computer Auditing· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
DBMS
University Research Chair
2009· book-chapter· en· Encyclopedia of Database Systems· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Business Intelligence Systems and Fraud Opportunity
Clark Hampton, Theophanis C. Stratopoulos
2012· article· en· Academy of Management Proceedings· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
Open Source BI: A Market Overview
Steve Holub
2009· article· en· ˜The œopen source business resource· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
eLearning Analytics Governance Modeling
Noureddine Elouazizi
2013· article· en· E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
How to Organize the Data Loading of SAP BI
Gaofeng Deng
2009· article· en· Microcomputer applications· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
afffundunlabeled
AI Governance in Academia: Guidelines for Generative AI
Clayton Peterson, M. Deschênes
2025· article· en· Proceedings of the ... International Florida Artificial Intelligence Research Society Conference· Business, Management and Accounting
machine prediction:candidate · metaresearchconsensus · none
0
citations
aboutno affunlabeled
Release: CiRBA Data Center Intelligence 6.0
Kenneth van Surksum
2010· article· en· www.virtualization.info· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
The Need for Data Standardization intheFood Supply Chain
Mitra Kaviani, Rozita Dara, Jeffrey M. Farber
2022· book-chapter· en· Food microbiology and food safety· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Exploring power BI for business intelligence advancements
Lokesh Chouhan, A Parashar, Abhinav Goyal, Vishal Shrivastava, Akhil Pandey
2024· article· en· AIP conference proceedings· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
fundno affunlabeled
SoCS 2013 Organization
Malte Helmert, Gabriele Röger
2021· article· en· Proceedings of the International Symposium on Combinatorial Search· Business, Management and Accounting
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
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