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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 34 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.

venueno affunlabeled
The TALP participation at TAC-KBP 2013
Alicia Ageno, Pere Ramon Comas Umbert, Ali Naderi, Horacio Rodríguez Hontoria, Jorge Turmo Borras
2013· article· en· Theory and applications of categories· Computer Science
distilled prediction:candidate · noneconsensus · none
2
citations
aboutno affno abstractunlabeled
QA System Metis Based on Semantic Graph Matching at NTCIR 6.
Minoru Harada, Yuhei Kato, Kazuaki Takehara, Masatsuna Kawamata, Sugimura Kazunori, Junichi Kawaguchi
2007· article· en· NTCIR· Computer Science
distilled prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Towards Neural Language Evaluators
Hassan Kané, Yusuf Kocyigit, Pelkins Ajanoh, Ali Abdalla, Mohamed Coulibali
2019· preprint· en· arXiv (Cornell University)· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
2
citations
afffundunlabeled
On Losses for Modern Language Models
Stéphane Aroca-Ouellette, Frank Rudzicz
2020· preprint· en· Computer Science
distilled prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
QuOTeS: Query-Oriented Technical Summarization
Juan Ramirez-Orta, Eduardo Xamena, Ana Gabriela Maguitman, Axel J. Soto, Flavia P. Zanoto, Evangelos Milios
2023· book-chapter· en· Lecture notes in computer science· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
2
citations
affunlabeled
GUCAS at TREC 2011 Microblog Track.
Xin Zhang, Kai Hui, Ben He, Tiejian Luo
2011· article· en· Text REtrieval Conference· Computer Science
distilled prediction:candidate · insufficient_payloadconsensus · insufficient_payload
2
citations
affno abstractunlabeled
Word Embedding Bias in Large Language Models
Poomrapee Chuthamsatid, Shera Potka, Alex Thomo
2025· book-chapter· en· Communications in computer and information science· Computer Science
distilled prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Spotify at the TREC 2020 Podcasts Track: Segment Retrieval.
Yongze Yu, Jussi Karlgren, Ann Clifton, Md. Iftekhar Tanveer, Rosie Jones, Hamed Bonab
2020· article· en· Text REtrieval Conference· Computer Science
distilled prediction:candidate · metaepi_narrow+insufficient_payloadconsensus · none
2
citations
affunlabeled
SmartBench
Abdelghny Orogat, Ahmed El-Roby
2022· article· en· Proceedings of the VLDB Endowment· Computer Science
distilled prediction:candidate · noneconsensus · none
2
citations
affunlabeled
WNED datasets and results
Zhaochen Guo, Denilson Barbosa
2017· dataset· en· Borealis· Computer Science
distilled prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Cooking Up a Neural-based Model for Recipe Classification
Elham Mohammadi, Nada Naji, Louis Marceau, Marc Queudot, Éric Charton, Leila Kosseim +1 more
2020· article· en· Language Resources and Evaluation· Computer Science
distilled prediction:candidate · noneconsensus · none
2
citations

How this was built: Screen · Findings · About