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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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Authorship Attribution and Profiling
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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
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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.

216 results · 1 filter active ·
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20022025
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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.
216 works in the cohort · of 4,299,418page 1 of 5

Labels cover 0 of 216 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 216 of 216 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.

affno abstractunlabeled
Towards an integrated e-mail forensic analysis framework
Rachid Hadjidj, Mourad Debbabi, Hakim Lounis, Farkhund Iqbal, Adam Szporer, Djamel Benredjem
2009· article· en· Digital Investigation· Computer Science
machine prediction:candidate · noneconsensus · none
86
citations
afffundunlabeled
Code Authorship Attribution
Vaibhavi Kalgutkar, Ratinder Kaur, Hugo Gonzalez, Natalia Stakhanova, Alina Matyukhina
2019· review· en· ACM Computing Surveys· Computer Science
machine prediction:candidate · noneconsensus · none
86
citations
affunlabeled
Authorship verification using deep belief network systems
Marcelo Luiz Brocardo, Issa Traoré, Isaac Woungang, Mohammad S. Obaidat
2017· article· en· International Journal of Communication Systems· Computer Science
machine prediction:candidate · noneconsensus · none
63
citations
affunlabeled
Web-based inference detection
Jessica Staddon, Philippe Golle, Bryce Zimny
2007· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
41
citations
affunlabeled
SynTF
Benjamin Weggenmann, Florian Kerschbaum
2018· article· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
33
citations
afffundunlabeled
Toward a science of science fiction
Ryan Nichols, Justin Lynn, Benjamin Grant Purzycki
2014· article· en· Scientific Study of Literature· Computer Science
machine prediction:candidate · noneconsensus · none
28
citations
affunlabeled
Arabic Authorship Attribution
Malik H. Altakrori, Farkhund Iqbal, Benjamin C. M. Fung, Steven H. H. Ding, Abdallah Tubaishat
2018· article· en· ACM Transactions on Asian and Low-Resource Language Information Processing· Computer Science
machine prediction:candidate · noneconsensus · none
23
citations
affunlabeled
Herbert west: deanonymizer
Mihir Nanavati, Nathan Taylor, William Aiello, Andrew Warfield
2011· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
19
citations
affno abstractunlabeled
Genre as noise: noise in genre
Andrea Stubbe, Christoph Ringlstetter, Klaus U. Schulz
2007· article· en· International Journal on Document Analysis and Recognition (IJDAR)· Computer Science
machine prediction:candidate · noneconsensus · none
18
citations

How this was built: Screen · Findings · About