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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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Personal Information Management and User Behavior
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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
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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.

465 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.
465 works in the cohort · of 4,299,418page 1 of 10

Labels cover 5 of 465 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 465 of 465 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
Cognitive Offloading
Evan F. Risko, Sam J. Gilbert
2016· review· en· Trends in Cognitive Sciences· Decision Sciences
machine prediction:candidate · noneconsensus · none
933
citations
affunlabeled
It's on my other computer!
David Dearman, Jeffery S. Pierce
2008· article· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
188
citations
affunlabeled
Dips and ceilings
Joey Scarr, Andy Cockburn, Carl Gutwin, Philip Quinn
2011· article· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
116
citations
affunlabeled
Hunter gatherer
m.c. schraefel, Yuxiang Zhu, David Modjeska, Daniel Wigdor, Shengdong Zhao
2002· article· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
108
citations
affunlabeled
AROMA
Adam Bodnar, Richard Corbett, Dmitry Nekrasovski
2004· article· en· Decision Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
105
citations
affunlabeled
The sky is not the limit
Bogdan Vasilescu, Kelly Blincoe, Qi Xuan, Casey Casalnuovo, Daniela Damian, Prémkumar Dévanbu +1 more
2016· article· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
78
citations
fundno affunlabeled
ProactiveTasks
Nikola Banović, Christina Brant, Jennifer Mankoff, Anind K. Dey
2014· article· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
71
citations
affunlabeled
Reinventing the inbox
Jacek Gwizdka
2002· article· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
68
citations
affgemma · no categorygpt · no categorymodels split
The ubiquitous digital file: A review of file management research
Jesse David Dinneen, Charles‐Antoine Julien
2019· review· en· Journal of the Association for Information Science and Technology· Decision Sciences
machine prediction:candidate · noneconsensus · none
66
citations
affunlabeled
Exploring multi-session web tasks
Bonnie Ma Kay, Carolyn Watters
2008· article· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
63
citations
affunlabeled
Ambient help
Justin Matejka, Tovi Grossman, George Fitzmaurice
2011· article· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
60
citations
afffundunlabeled
Design Recommendations for Self-Monitoring in the Workplace
André N. Meyer, Gail C. Murphy, Thomas Zimmermann, Thomas Fritz
2017· article· en· Proceedings of the ACM on Human-Computer Interaction· Decision Sciences
machine prediction:candidate · noneconsensus · none
59
citations
affno abstractunlabeled
How Do Developers React to RESTful API Evolution?
Shaohua Wang, Iman Keivanloo, Ying Zou
2014· book-chapter· en· Lecture notes in computer science· Decision Sciences
machine prediction:candidate · noneconsensus · none
57
citations
affunlabeled
Using chatbots to aid transition
Sofy Carayannopoulos
2017· article· en· International Journal of Information and Learning Technology· Decision Sciences
machine prediction:candidate · noneconsensus · none
52
citations
afffundunlabeled
Hoarding and Minimalism
Francesco Vitale, Izabelle Janzen, Joanna McGrenere
2018· article· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
51
citations

How this was built: Screen · Findings · About