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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.

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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.

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 21 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.

affno abstractunlabeled
Latent word context model for information retrieval
Bernard Brosseau-Villeneuve, Jian‐Yun Nie, Noriko Kando
2013· article· en· Information Retrieval· Computer Science
distilled prediction:candidate · scholarly_communication+insufficient_payloadconsensus · none
8
citations
afffundunlabeled
Local Structure Matters Most: Perturbation Study in NLU
Louis Clouâtre, Prasanna Parthasarathi, Amal Zouaq, Sarath Chandar
2022· article· en· Findings of the Association for Computational Linguistics: ACL 2022· Computer Science
distilled prediction:candidate · noneconsensus · none
8
citations
affunlabeled
Parallelizing Legendre Memory Unit Training
Narsimha Chilkuri, Chris Eliasmith
2021· preprint· en· arXiv (Cornell University)· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
8
citations
affunlabeled
Early Stage Sparse Retrieval with Entity Linking
Dahlia Shehata, Negar Arabzadeh, Charles L. A. Clarke
2022· article· en· Proceedings of the 31st ACM International Conference on Information & Knowledge Management· Computer Science
distilled prediction:candidate · noneconsensus · none
8
citations
venueno affunlabeled
The Italica System at TAC 2008 Opinion Summarization Task
Fermín L. Cruz, José A. Troyano, F. Javier Ortega, Fernando Enríquez
2008· article· en· Theory and applications of categories· Computer Science
distilled prediction:candidate · noneconsensus · none
8
citations
venueno affunlabeled
Multi-Label Classification in Patient-Doctor Dialogues With the RoBERTa-WWM-ext + CNN (Robustly Optimized Bidirectional Encoder Representations From Transformers Pretraining Approach With Whole Word Masking Extended Combining a Convolutional Neural Network) Model: Named Entity Study
Yuanyuan Sun, Dongping Gao, Xifeng Shen, Meiting Li, Jiale Nan, Weining Zhang
2022· article· en· JMIR Medical Informatics· Computer Science
distilled prediction:candidate · noneconsensus · none
7
citations
affno abstractunlabeled
Natural Language Processing: An Overview
Hessam Amini, Farhood Farahnak, Leila Kosseim
2019· book-chapter· en· WORLD SCIENTIFIC eBooks· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communicationconsensus · none
7
citations
affno abstractunlabeled
Show us the model
Mark S. Seidenberg, Marc F. Joanisse
2003· review· en· Trends in Cognitive Sciences· Computer Science
distilled prediction:candidate · noneconsensus · none
7
citations

How this was built: Screen · Findings · About