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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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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.

923 results · 1 filter active ·
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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.
923 works in the cohort · of 4,299,418page 4 of 19

Labels cover 923 of 923 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 923 of 923 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.

affgemma · bibliometrics+metaresearchgpt · metaresearch+bibliometrics+scholarly_communicationmodels split
Co‐saved, co‐tweeted, and co‐cited networks
Fereshteh Didegah, Mike Thelwall
2018· article· en· Journal of the Association for Information Science and Technology· Decision Sciences
machine prediction:candidate · bibliometricsconsensus · none
21
citations
affgemma · bibliometricsgpt · bibliometricsmodels agree
Webometrics: An introduction to the special issue
Mike Thelwall, Liwen Vaughan
2004· article· en· Journal of the American Society for Information Science and Technology· Computer Science
machine prediction:candidate · bibliometricsconsensus · none
20
citations
aboutno affgemma · bibliometricsgpt · bibliometricsmodels agree
Telemedicine – a scientometric and density equalizing analysis
David A. Groneberg, Shaghayegh Rahimian, M. Bundschuh, Alexander Gerber, Beatrix Kloft
2015· article· en· Journal of Occupational Medicine and Toxicology· Medicine
machine prediction:candidate · bibliometricsconsensus · none
19
citations
afffundno abstractgemma · bibliometricsgpt · no categorymodels split
I publish, therefore I am. Or am I? A reply to A bibliometric investigation of life cycle assessment research in the web of science databases by Chen et al. (2014) and Mapping the scientific research on life cycle assessment: a bibliometric analysis by Hou et al. (2015)
Sandra Estrela
2015· article· en· The International Journal of Life Cycle Assessment· Environmental Science
machine prediction:candidate · metaresearch+bibliometricsconsensus · none
18
citations
aboutno affgemma · bibliometricsgpt · bibliometricsmodels split
Inventory Models in a Sustainable Supply Chain: A Bibliometric Analysis
Katherinne Salas-Navarro, Paula Serrano-Pájaro, Holman Ospina-Mateus, Ronald Zamora-Musa
2022· article· en· Sustainability· Business, Management and Accounting
machine prediction:candidate · bibliometricsconsensus · none
18
citations
affno abstractgemma · bibliometricsgpt · bibliometrics+metaresearchmodels split
Neophilia ranking of scientific journals
Mikko Packalén, Jay Bhattacharya
2016· article· en· Scientometrics· Decision Sciences
machine prediction:candidate · bibliometricsconsensus · none
18
citations
affgemma · bibliometricsgpt · bibliometricsmodels split
A multi-method bibliometric review of value co-creation research
Sumit Saxena, Amritesh Amritesh, Subhas C. Mishra, Bhasker Mukerji
2023· article· en· Management Research Review· Business, Management and Accounting
machine prediction:candidate · bibliometricsconsensus · none
18
citations
affgemma · metaresearch+bibliometricsgpt · metaresearch+bibliometricsmodels agree
Characteristics of ‘mega’ peer-reviewers
Danielle B. Rice, Ba’ Pham, Justin Presseau, Andrea C. Tricco, David Moher
2022· article· en· Research Integrity and Peer Review· Decision Sciences
machine prediction:candidate · metaresearch+bibliometricsconsensus · none
17
citations
aboutno affgemma · bibliometricsgpt · bibliometricsmodels split
A bibliometric analysis of income and cardiovascular disease
Ye Ding, Dingwan Chen, Xufen Ding, Guan Wang, Yuehua Wan, Qing Shen
2020· review· en· Medicine· Social Sciences
machine prediction:candidate · metaresearch+bibliometricsconsensus · none
17
citations

How this was built: Screen · Findings · About