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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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Artificial Intelligence in Law
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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.

413 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.
413 works in the cohort · of 4,299,418page 2 of 9

Labels cover 0 of 413 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 413 of 413 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
Semantic-Based Classification of Relevant Case Law
Juliano Rabelo, Miyoung Kim, Randy Goebel
2023· book-chapter· en· Lecture notes in computer science· Social Sciences
machine prediction:candidate · noneconsensus · none
13
citations
afffundunlabeled
JusticeBot
Hannes Westermann, Karim Benyekhlef
2023· article· en· Social Sciences
machine prediction:candidate · noneconsensus · none
12
citations
afffundunlabeled
Interpretable Low-Resource Legal Decision Making
Rohan Bhambhoria, Hui Liu, Samuel Dahan, Xiaodan Zhu
2022· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Social Sciences
machine prediction:candidate · noneconsensus · none
11
citations
aboutno affunlabeled
References to Artificial Intelligence in Canada's Court Cases
Channarong Intahchomphoo, André Vellino, Odd Erik Gundersen, Christian Tschirhart, Eslam Shaaban
2020· article· en· Legal Information Management· Social Sciences
machine prediction:candidate · noneconsensus · none
10
citations
affunlabeled
Scenario analytics
Jack G. Conrad, Khalid Al-Kofahi
2017· article· en· Social Sciences
machine prediction:candidate · noneconsensus · none
7
citations
affaboutunlabeled
Detection of Similar Legal Cases on Personal Injury
Jason Lam, Yuhao Chen, Farhana Zulkernine, Samuel Dahan
2021· article· en· 2021 International Conference on Data Mining Workshops (ICDMW)· Social Sciences
machine prediction:candidate · noneconsensus · none
6
citations
aboutno affunlabeled
Technology, Innovation and Access to Justice
Siddharth Peter de Souza, Maximilian Spohr
2021· book· en· Edinburgh University Press eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Large Language Models in Legal Systems: A Survey
Fatemeh Dehghani, Roya Dehghani, Yazdan Naderzadeh Ardebili, Shahryar Rahnamayan
2025· article· en· Humanities and Social Sciences Communications· Social Sciences
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Effects of XAI on Legal Process
Aileen Nielsen, Stavroula Skylaki, Milda Norkutė, Alexander Stremitzer
2023· article· en· Social Sciences
machine prediction:candidate · noneconsensus · none
6
citations
afffundno abstractunlabeled
SymboleoPC: checking properties of legal contracts
Alireza Parvizimosaed, Marco Roveri, Aidin Rasti, Amal Ahmed Anda, Sofana Alfuhaid, Daniel Amyot +2 more
2024· article· en· Software & Systems Modeling· Social Sciences
machine prediction:candidate · noneconsensus · none
6
citations

How this was built: Screen · Findings · About