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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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Formal Methods in Verification
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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.

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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.

1,244 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.
1,244 works in the cohort · of 4,299,418page 9 of 25

Labels cover 3 of 1,244 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 1,244 of 1,244 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
Using Learnt Clauses in maxsat
Jessica Davies, Jeremy Cho, Fahiem Bacchus
2010· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
9
citations
afffundunlabeled
Model Checking Using Description Logic
S. Ben-David, Richard Trefler, Grant Weddell
2008· article· en· Journal of Logic and Computation· Computer Science
machine prediction:candidate · noneconsensus · none
9
citations
fundno affunlabeled
Trace-checking signal-based temporal properties
Chaima Boufaied, Claudio Menghi, Domenico Bianculli, Lionel Briand, Yago Isasi Parache
2020· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
9
citations
affno abstractunlabeled
Speeding Up Assumption-Based SAT
Randy Hickey, Fahiem Bacchus
2019· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
9
citations
afffundunlabeled
Refinement patterns for ASTDs
Marc Frappier, Frédéric Gervais, Régine Laleau, Jérémy Milhau
2013· article· en· Formal Aspects of Computing· Computer Science
machine prediction:candidate · noneconsensus · none
9
citations
afffundno abstractunlabeled
The Configurable SAT Solver Challenge (CSSC)
Frank Hutter, Marius Lindauer, Adrian Balint, Sam Bayless, Holger H. Hoos, Kevin Leyton‐Brown
2016· preprint· en· Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
affno abstractunlabeled
Are Statecharts Finite Automata?
Han-Lin Lu, Sheng Yü
2009· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
affunlabeled
Minimisation and minimal realisation in Span(Graph)
Robert Rosebrugh, N. Sabadini, R. F. C. Walters
2004· article· en· Mathematical Structures in Computer Science· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
afffundunlabeled
Trace Diagnostics for Signal-Based Temporal Properties
Chaima Boufaied, Claudio Menghi, Domenico Bianculli, Lionel Briand
2023· article· en· IEEE Transactions on Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
affunlabeled
What packets may come
Karthikeyan Bhargavan, Satish Chandra, Peter J. McCann, Carl A. Gunter
2001· article· en· ACM SIGPLAN Notices· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations

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