MétaCan
Menu
Cohort builder

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.

Search term
Author
Year range
Sort
Language
Type
Field
Venue
Topic
Mobile Crowdsensing and Crowdsourcing
Retraction
Abstract
Evidence source
Study design
Label agreement
Label status

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.

449 results · 1 filter active ·
Results by year
20002025
Publication date
Categories
Machine labels · sparse coverage
Evidence
Language
Type
Citations
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
449 works in the cohort · of 4,299,418page 3 of 9

Labels cover 3 of 449 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 449 of 449 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

fundno affunlabeled
Eliciting and Learning with Soft Labels from Every Annotator
Katherine M. Collins, Umang Bhatt, Adrian Weller
2022· article· en· Proceedings of the AAAI Conference on Human Computation and Crowdsourcing· Computer Science
distilled prediction:candidate · stsconsensus · none
26
citations
affunlabeled
Assessing Top- Preferences
Charles L. A. Clarke, Alexandra Vtyurina, Mark D. Smucker
2021· article· en· ACM Transactions on Information Systems· Computer Science
distilled prediction:candidate · scholarly_communicationconsensus · none
25
citations
afffundunlabeled
A Gamification Framework for Sensor Data Analytics
Alexandra L’Heureux, Katarina Grolinger, Wilson A. Higashino, Miriam A. M. Capretz
2017· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
25
citations
affunlabeled
Collaborative crowdsourcing with crowd4U
Kosetsu Ikeda, Atsuyuki Morishima, Habibur Rahman, Senjuti Basu Roy, Saravanan Thirumuruganathan, Sihem Amer-Yahia +1 more
2016· article· en· Proceedings of the VLDB Endowment· Computer Science
distilled prediction:candidate · noneconsensus · none
24
citations
affunlabeled
On Actively Teaching the Crowd to Classify
Adish Singla, Ilija Bogunovic, Gábor Bartók, Amin Karbasi, Andreas Krause
2013· article· en· Infoscience (Ecole Polytechnique Fédérale de Lausanne)· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communicationconsensus · none
23
citations
affunlabeled
Bots for pull requests
Mairieli Wessel, Ahmad Abdellatif, Igor Wiese, Tayana Conte, Emad Shihab, Marco Aurélio Gerosa +1 more
2022· article· en· Proceedings of the 44th International Conference on Software Engineering· Computer Science
distilled prediction:candidate · noneconsensus · none
23
citations
afffundunlabeled
How many crowdsourced workers should a requester hire?
Arthur Carvalho, Stanko Dimitrov, Kate Larson
2016· article· en· Annals of Mathematics and Artificial Intelligence· Computer Science
distilled prediction:candidate · noneconsensus · none
20
citations
afffundunlabeled
Learn or Earn? - Intelligent Task Recommendation for Competitive Crowdsourced Software Development
Muhammad Rezaul Karim, Ye Yang, David W. Messinger, Guenther Ruhe
2018· article· en· Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences· Computer Science
distilled prediction:candidate · metaepi_narrow+sts+scholarly_communication+open_scienceconsensus · none
19
citations
affunlabeled
Taking Search to Task
Chirag Shah, Ryen W. White, Paul Thomas, Bhaskar Mitra, Shawon Sarkar, Nicholas J. Belkin
2023· article· en· Computer Science
distilled prediction:candidate · insufficient_payloadconsensus · none
19
citations
affunlabeled
NetEase Cloud Music Data
Dennis Zhang, Ming Hu, Xiaofei Liu, Yuxiang Wu, Yong Li
2020· article· en· Manufacturing & Service Operations Management· Computer Science
distilled prediction:candidate · noneconsensus · none
19
citations
afffundunlabeled
Coordinating Crowd-Sourced Services
Ahmed Abdel Moamen, Nadeem Jamali
2014· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
19
citations
affunlabeled
Beyond Micro-Tasks
Roman Lukyanenko, Jeffrey Parsons
2018· article· en· Journal of Database Management· Computer Science
distilled prediction:candidate · noneconsensus · none
17
citations

How this was built: Screen · Findings · About