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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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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.

2,769 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.
2,769 works in the cohort · of 4,299,418page 17 of 56

Labels cover 6 of 2,769 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 2,769 of 2,769 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affunlabeled
Using In-Context Learning to Improve Dialogue Safety
Nicholas Meade, Spandana Gella, Devamanyu Hazarika, Prakhar Gupta, Di Jin, Siva Reddy +2 more
2023· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
12
citations
affunlabeled
Robust Cross-lingual Embeddings from Parallel Sentences
Ali Reza Sabet, Prakhar Gupta, Jean-Baptiste Cordonnier, Robert West, Martin Jaggi
2019· preprint· en· arXiv (Cornell University)· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
12
citations
afffundunlabeled
Identify Event Causality with Knowledge and Analogy
Sifan Wu, Ruihui Zhao, Yefeng Zheng, Jian Pei, Bang Liu
2023· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
distilled prediction:candidate · noneconsensus · none
12
citations
venueno affunlabeled
CLASSY and TAC 2008 Metrics.
John M. Conroy, Judith D. Schlesinger
2008· article· en· Theory and applications of categories· Computer Science
distilled prediction:candidate · noneconsensus · none
12
citations
fundno affunlabeled
Probing as Quantifying Inductive Bias
Alexander Immer, Lucas Torroba Hennigen, Vincent Fortuin, Ryan Cotterell
2022· article· en· Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)· Computer Science
distilled prediction:candidate · metaresearchconsensus · none
12
citations
affunlabeled
Modeling Autobiographical Memory for Believable Agents
Andrew B Kope, Caroline Rose, Michael Katchabaw
2013· article· en· Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment· Computer Science
distilled prediction:candidate · noneconsensus · none
11
citations
affunlabeled
Predicting Attention Sparsity in Transformers
Marcos Treviso, António Góis, Patrick Fernandes, Erick Fonseca, André F. T. Martins
2022· preprint· en· Computer Science
distilled prediction:candidate · noneconsensus · none
11
citations

How this was built: Screen · Findings · About