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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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Information Science and Libraries
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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.

133 results · 1 filter active ·
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20012025
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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.
133 works in the cohort · of 4,299,418page 1 of 3

Labels cover 1 of 133 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 133 of 133 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.

venueno affunlabeled
Dimensão Ética da Mediação da Informação
Henriette Ferreira Gomes
2021· article· en· The International Review of Information Ethics· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Para que serve o editorial? Para desejar Feliz 2020?
Marcelo Amaral, Bruno Brandão Fischer, Virgílio Cézar da Silva e Oliveira, Rodrigo da Silva Carvalho
2019· article· pt· Revista de Administração Sociedade e Inovação· Computer Science
machine prediction:candidate · noneconsensus · none
3
citations
affunlabeled
Hackers no Brasil
André Lemos, Simone Seara, Wilson Pérsio
2008· article· pt· Revista Contracampo· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Controvérsias e divulgação científica
Luisa Massarani, Martha Marandino, Marina Ramalho e Silva
2021· article· pt· Journal of Science Communication América Latina· Computer Science
machine prediction:candidate · stsconsensus · none
1
citations
aboutno affunlabeled
FERRAMENTAS PARA LETRAMENTO ACADÊMICO
Eliane Gouvêa Lousada, Luzia Bueno
2018· article· pt· CIET:EnPED· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Apresentação
Leandra Inês Seganfredo Santos, Cláudia Hilsdorf Rocha, Neusa Inês ́Philippsen
2017· article· pt· Revista de Letras Norte mentos· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
BETWEEN PRESERVATION AND ACCESS
Lidia Eugenia Cavalcante Lima
2025· article· pt· Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
NOTA DO EDITOR
Núcleo de Editoração
2003· article· pt· LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
NOTICE: AVIS:
2009· article· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
VAMOS FALAR DE NOVA BIBLIOTECONOMIA
Emanuelle Geórgia Amaral Ferreira, Carlos Alberto Ávila Araújo
2017· article· pt· Anais do Congresso Brasileiro de Biblioteconomia, Documentação e Ciência da Informação - FEBAB· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About