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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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Supply Chain Resilience and Risk 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
fundfunder
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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.

869 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.
869 works in the cohort · of 4,299,418page 8 of 18

Labels cover 1 of 869 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 869 of 869 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
A Framework for Smart Supply Chain Risk Assessment
Khalid Khan, Abbas Keramati
2023· article· en· International Journal of Information Systems and Supply Chain Management· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
4
citations
venueno affno abstractunlabeled
Building Cyber-Resilience into Supply Chains
Adrian Davis
2015· article· en· Technology Innovation Management Review· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Uncertainty regulation and adaptable supply chain planning
Sourav Sengupta, Patrik Jönsson, Heidi C. Dreyer, Riikka Kaipia, Thomas Y. Choi
2025· article· en· International Journal of Operations & Production Management· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Global Sustainable Supplier Selection
Anjali Awasthi, Stefan Gold
2019· book-chapter· en· Advances in logistics, operations, and management science book series· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
4
citations
venueno affunlabeled
Identifying and Assessing the Risks in the Supply Chain
Seyyed Mohammad Seyyed Alizadeh Ganji, Mohammad Hayati
2016· article· en· Modern Applied Science· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Analytics for Nonprofits
Caroline M. Mularz, M. Ali Ülkü
2014· book-chapter· en· IGI Global eBooks· Business, Management and Accounting
machine prediction:candidate · insufficient_payloadconsensus · none
3
citations

How this was built: Screen · Findings · About