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
scientometrics and bibliometrics research
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.

2,100 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.
2,100 works in the cohort · of 4,299,418page 2 of 42

Labels cover 193 of 2,100 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 2,100 of 2,100 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.

affunlabeled
The incidence and role of negative citations in science
Christian Catalini, Nicola Lacetera, Alexander Oettl
2015· article· en· Proceedings of the National Academy of Sciences· Decision Sciences
machine prediction:candidate · metaresearch+bibliometricsconsensus · none
189
citations
affunlabeled
The decline in the concentration of citations, 1900–2007
Vincent Larivière, Yves Gingras, Éric Archambault
2009· article· en· Journal of the American Society for Information Science and Technology· Decision Sciences
machine prediction:candidate · bibliometricsconsensus · none
179
citations
affunlabeled
Author-Reviewer Homophily in Peer Review
Dakota Murray, Kyle Siler, Vincent Larivière, Wei Mun Chan, Andy Collings, Jennifer L Raymond +1 more
2018· preprint· en· bioRxiv (Cold Spring Harbor Laboratory)· Decision Sciences
machine prediction:candidate · metaresearch+bibliometricsconsensus · none
178
citations
affunlabeled
Participation in the global knowledge commons
Leslie Chan, Sely Costa
2005· article· en· New Library World· Decision Sciences
machine prediction:candidate · scholarly_communication+open_scienceconsensus · none
165
citations
afffundgemma · metaresearch+scholarly_communicationgpt · research_integrity+scholarly_communicationmodels split
What is a predatory journal? A scoping review
Kelly D. Cobey, Manoj M. Lalu, Becky Skidmore, Nadera Ahmadzai, Agnes Grudniewicz, David Moher
2018· review· en· F1000Research· Decision Sciences
machine prediction:candidate · metaresearch+research_integrityconsensus · none
154
citations
afffundvenuegemma · metaresearch+bibliometrics+research_integritygpt · metaresearch+bibliometrics+scholarly_communication+research_integritymodels split
How predatory journals leak into PubMed
Andrea Manca, David Moher, Lucia Cugusi, Zeevi Dvir, Franca Deriu
2018· article· en· Canadian Medical Association Journal· Decision Sciences
machine prediction:candidate · metaresearch+bibliometrics+research_integrityconsensus · none
146
citations
affunlabeled
The Evaluation of Large Research Initiatives
William M. K. Trochim, Stephen E. Marcus, Louise C. Mâsse, Richard P. Moser, Patrick C. Weld
2008· article· en· American Journal of Evaluation· Decision Sciences
machine prediction:candidate · metaresearch+bibliometricsconsensus · metaresearch
144
citations
afffundgemma · metaresearch+research_integrity+scholarly_communicationgpt · metaresearch+research_integritymodels split
What is a predatory journal? A scoping review
Kelly D. Cobey, Manoj M. Lalu, Becky Skidmore, Nadera Ahmadzai, Agnes Grudniewicz, David Moher
2018· review· en· F1000Research· Decision Sciences
machine prediction:candidate · metaresearch+research_integrityconsensus · none
141
citations
venueno affunlabeled
Effective Strategies for Increasing Citation Frequency
Nader Ale Ebrahim, Hadi Salehi, Mohamed Amin Embi, Farid Habibi Tanha, Hossein Gholizadeh, Seyed Mohammad Motahar +1 more
2013· article· en· International Education Studies· Decision Sciences
machine prediction:candidate · metaresearch+bibliometricsconsensus · none
140
citations
affno abstractunlabeled
Analysis and Visualization of Citation Networks
Dangzhi Zhao, Andreas Strotmann
2015· article· en· Synthesis lectures on information concepts, retrieval, and services· Decision Sciences
machine prediction:candidate · bibliometricsconsensus · none
136
citations
affunlabeled
The gendered nature of authorship
Chaoqun Ni, Elise Smith, Haimiao Yuan, Vincent Larivière, Cassidy R. Sugimoto
2021· article· en· Science Advances· Decision Sciences
machine prediction:candidate · metaresearch+bibliometrics+research_integrityconsensus · none
129
citations
affno abstractunlabeled
Public use and public funding of science
Yian Yin, Yuxiao Dong, Kuansan Wang, Dashun Wang, Benjamin F. Jones
2022· article· en· Nature Human Behaviour· Decision Sciences
machine prediction:candidate · metaresearch+bibliometricsconsensus · none
120
citations

How this was built: Screen · Findings · About