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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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Technology Adoption and User Behaviour
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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.

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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.

1,648 results · 1 filter active ·
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20002025
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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.
1,648 works in the cohort · of 4,299,418page 27 of 33

Labels cover 4 of 1,648 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 1,648 of 1,648 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.

aboutno affunlabeled
The Future of SMS Technology: Disruptive Technology
Cik Ku Haroswati Binti Che Ku Yahaya
2018· article· en· WSEAS Transactions on Information Science and Applications archive· Decision Sciences
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
10.51847/vRzBGqdJ0K
2000· article· en· Time to knit· Decision Sciences
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Globalization and Relevant Strategy for E-Commerce
Mahmud Akhter Shareef, Yogesh K. Dwivedi, Michael D. Williams, Nitish Singh
2010· book-chapter· en· IGI Global eBooks· Decision Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Orientation Of It Towards Human Being
Franz Plochberger
2016· report· en· Phaidra (Universität Wien)· Decision Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Published by Canadian
2016· article· en· Decision Sciences
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Understanding Customers' Continuance Intention
Bangaly Kaba
2021· article· en· ACM SIGMIS Database the DATABASE for Advances in Information Systems· Decision Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Technology Adoption and Academic Development
Heather Kanuka, Nathasja Saranchuk
2011· article· en· E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education· Decision Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
‘Pragmatic Evaluation’
Richard E. Scott
2012· book-chapter· en· IGI Global eBooks· Decision Sciences
machine prediction:candidate · metaresearchconsensus · none
0
citations
venueno affunlabeled
Adoption of Instant Messenger: An Empirical Investigation
Arun Kumar Tarofder, Umme Salma Sultana, Siti Khalidah Binti Md Yusoff, Sultan Rehman Sherief, Ahasanul Haque
2019· article· en· Journal of Reviews on Global Economics· Decision Sciences
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About