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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.

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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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Foundations and Trends® in Human–Computer Interaction
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Retraction
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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
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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.

9 results · 1 filter active ·
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20092025
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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.
9 works in the cohort · of 4,299,418page 1 of 1

Labels cover 0 of 9 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 9 of 9 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affunlabeled
Exertion Games
Florian Mueller, Rohit Ashok Khot, Kathrin Gerling, Regan L. Mandryk
2016· article· en· Foundations and Trends® in Human–Computer Interaction· Computer Science
distilled prediction:candidate · noneconsensus · none
70
citations
affunlabeled
Ubiquitous Computing for Capture and Access
Khai N. Truong, Gillian R. Hayes
2009· article· en· Foundations and Trends® in Human–Computer Interaction· Computer Science
distilled prediction:candidate · scholarly_communicationconsensus · none
48
citations
affunlabeled
Modes of Uncertainty in HCI
Robert Soden, Laura Devendorf, Richmond Y. Wong, Yoko Akama, Ann Light
2022· article· en· Foundations and Trends® in Human–Computer Interaction· Social Sciences
distilled prediction:candidate · insufficient_payloadconsensus · none
32
citations
affunlabeled
Readability Research: An Interdisciplinary Approach
Sofie Beier, Sam Berlow, Esat Boucaud, Zoya Bylinskii, Tianyuan Cai, Jenae Cohn +22 more
2022· article· en· Foundations and Trends® in Human–Computer Interaction· Computer Science
distilled prediction:candidate · stsconsensus · none
21
citations
affunlabeled
WaterHCI: Water in Human-Computer Interaction
Maria Montoya Vega, Ian Smith, Christal Clashing, Rakesh Patibanda, Swamy Ananthanarayan, Sarah Jane Pell +1 more
2024· article· en· Foundations and Trends® in Human–Computer Interaction· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communicationconsensus · none
6
citations

How this was built: Screen · Findings · About