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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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Proceedings of the ACM on Management of Data
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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.

43 results · 1 filter active ·
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20232025
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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.
43 works in the cohort · of 4,299,418page 1 of 1

Labels cover 0 of 43 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 43 of 43 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
Reliable Text-to-SQL with Adaptive Abstention
Kaiwen Chen, Yueting Chen, Nick Koudas, Xiaohui Yu
2025· article· en· Proceedings of the ACM on Management of Data· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
affunlabeled
dbET: Execution Time Distribution-based Plan Selection
Yifan Li, Xiaohui Yu, Nick Koudas, Shu Lin, Calvin Sun, Chong Chen
2023· article· en· Proceedings of the ACM on Management of Data· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
affunlabeled
Reservoir Sampling over Joins
Binyang Dai, Xiao Hu, Ke Yi
2024· article· en· Proceedings of the ACM on Management of Data· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Wii: Dynamic Budget Reallocation In Index Tuning
Xiaoying Wang, Wentao Wu, Chi Wang, Vivek Narasayya, Surajit Chaudhuri
2024· article· en· Proceedings of the ACM on Management of Data· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Data Acquisition for Improving Model Confidence
Yifan Li, Xiaohui Yu, Nick Koudas
2024· article· en· Proceedings of the ACM on Management of Data· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
aboutno affunlabeled
Rethink Query Optimization in HTAP Databases
Haoze Song, Wenchao Zhou, Feifei Li, X. Peng, Heming Cui
2023· article· en· Proceedings of the ACM on Management of Data· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
On the Feasibility of Forgetting in Data Streams
A. Pavan, Sourav Chakraborty, N. V. Vinodchandran, Kuldeep S. Meel
2024· article· en· Proceedings of the ACM on Management of Data· Computer Science
machine prediction:candidate · noneconsensus · none
3
citations
affunlabeled
A faster FPRAS for #NFA
Kuldeep S. Meel, Sourav Chakraborty, Umang Mathur
2024· article· en· Proceedings of the ACM on Management of Data· Computer Science
machine prediction:candidate · noneconsensus · none
3
citations
affunlabeled
Topology-aware Parallel Joins
Xiao Hu, Paraschos Koutris
2024· article· en· Proceedings of the ACM on Management of Data· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations

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