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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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Sentiment Analysis and Opinion Mining
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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.

797 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.
797 works in the cohort · of 4,299,418page 5 of 16

Labels cover 0 of 797 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 797 of 797 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affunlabeled
Text to Ideology or Text to Party Status?
Graeme Hirst, Yaroslav Riabinin, Jory Graham, Magali Boizot-Roche, Colin Morris
2014· book-chapter· en· Discourse approaches to politics, society and culture· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
21
citations
affunlabeled
Sentence Subjectivity Analysis in Social Domains
Mostafa Karamibekr, Ali A. Ghorbani
2013· article· en· 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)· Computer Science
distilled prediction:candidate · metaepi_narrow+insufficient_payloadconsensus · none
21
citations
affunlabeled
Emotion Intensities in Tweets
Saif M. Mohammad, Felipe Bravo-Márquez
2017· preprint· en· Computer Science
distilled prediction:candidate · noneconsensus · none
20
citations
affno abstractunlabeled
Query-Based Summarization of Customer Reviews
Olga Feiguina, Guy Lapalme
2007· book-chapter· en· Lecture notes in computer science· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
19
citations
aboutno affunlabeled
Tweets Sentiment Analysis During COVID-19 Pandemic
Maha A. Alanezi, Nabil M. Hewahi
2020· article· en· 2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI)· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communicationconsensus · none
18
citations
affunlabeled
OutdoorSent
Wyverson Bonasoli de Oliveira, Leyza Baldo Dorini, Rodrigo Minetto, Thiago H. Silva
2020· article· en· ACM Transactions on Information Systems· Computer Science
distilled prediction:candidate · insufficient_payloadconsensus · none
17
citations
venueno affunlabeled
Spam and Sentiment Detection in Arabic Tweets Using MARBERT Model
Abrar Alotaibi, Atta Rahman, Raheel Alhaza, Wala Alkhalifa, Narjes Alhajjaj, Atheer Alharthi +3 more
2022· article· en· Mathematical Modelling and Engineering Problems· Computer Science
distilled prediction:candidate · noneconsensus · none
17
citations
affunlabeled
Mining Opinion Leaders in Big Social Network
Yi-Cheng Chen, Yi‐Hsiang Chen, Chia-Hao Hsu, Hao‐Jun You, Jianquan Liu, Xin Huang
2017· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
16
citations
affunlabeled
Identifying purpose behind electoral tweets
Saif M. Mohammad, Svetlana Kiritchenko, Joel Martin
2013· article· en· Computer Science
distilled prediction:candidate · insufficient_payloadconsensus · insufficient_payload
15
citations

How this was built: Screen · Findings · About