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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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Text and Document Classification Technologies
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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.

374 results · 1 filter active ·
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20002025
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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.
374 works in the cohort · of 4,299,418page 6 of 8

Labels cover 2 of 374 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 374 of 374 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
Performance Comparison of Qur’anic Search Engines
Saqib Hakak, Gulshan Amin Gilkar, Wazir Zada Khan
2020· article· en· 2020 International Conference on Computing and Information Technology (ICCIT-1441)· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Social Classification
Reda Alhajj, Jon Rokne
2018· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Tapor: Building a Portal for Text Analysis
Geoffrey Rockwell
2006· book-chapter· en· University of Calgary Press eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Multi-Mask Label Mapping for Prompt-Based Learning
Jirui Qi, Richong Zhang, Jaein Kim, Junfan Chen, Wenyi Qin, Yongyi Mao
2023· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Editorial
A. H. M. Zahirul Alam
2021· editorial· en· IIUM Engineering Journal· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
Feature Extraction, Selection, and Creation
Mohamed Cheriet, Nawwaf Kharma, Cheng‐Lin Liu, Ching Y. Suen
2007· other· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
fundaboutno affunlabeled
9780472902422.pdf
2021· other· en· OAPEN (The OAPEN Foundation)· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
Multi-graph embedding for partial label learning
Hongyan Li, Chi‐Man Vong, Zhonglin Wan
2023· article· en· Neural Computing and Applications· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Briefly Noted
2012· article· en· Computational Linguistics· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations

How this was built: Screen · Findings · About