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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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Auditing, Earnings Management, Governance
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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
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

3,740 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.
3,740 works in the cohort · of 4,299,418page 74 of 75

Labels cover 11 of 3,740 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 3,740 of 3,740 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
Book Reviews
Ashok V. Desai, Meghnad Desai, Murray Wolfson, Jeffrey T. Young, Michel Juillard, Pankaj Ghemawat +33 more
2000· article· en· Journal of Economic Literature· Business, Management and Accounting
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
venueno affunlabeled
Business Strategy and R&D Expenditures
Han Li
2020· article· en· International Journal of Financial Research· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
IFRS Adoption and Bank Performance in Nigeria and Canada Banks
T Ajibade Ayodeji, Nyikyaa Terdoo Phoebe, Nyikyaa Nguavese Miriam
2019· article· en· HAL (Le Centre pour la Communication Scientifique Directe)· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Canadian IFRS Strategy and New GAAP Systems
紀生 山本, ノリオ ヤマモト, Yamamoto Norio
2016· article· ja· Institutional Repositories DataBase (IRDB)· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Investor overconfidence and stock price crash risk
Hasibul Chowdhury, Khoa Hoang, Ronghong Huang, Xiaowen Peng, Suichen Xu
2025· article· en· Journal of Accounting Literature· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Acknowledgments
2004· article· en· Business, Management and Accounting
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Summary
2005· article· en· Business, Management and Accounting
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
Media Sentiment and Shareholder Litigation
Richard A. Cazier, Jianning Huang, Jeff L. McMullin, Fuzhao Zhou
2025· article· en· Journal of Business Finance &amp Accounting· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Are earnings more volatile under IFRS?
Bhopinder Singh Gill
2009· dissertation· en· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Comments on Proposed SEC 2010-2015 Draft Strategic Plan
Robert J. Bloomfield, Theodore E. Christensen, Jonathan Glover, Susan F. Haka, Karim Jamal, James A. Ohlson +4 more
2009· article· en· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About