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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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Academic Publishing and Open Access
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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.

1,650 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.
1,650 works in the cohort · of 4,299,418page 2 of 33

Labels cover 37 of 1,650 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 1,650 of 1,650 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
Ten myths around open scholarly publishing
Jonathan Tennant, Harry Crane, Tom Crick, Jacinto Dávila, Asura Enkhbayar, Jo Havemann +10 more
2019· preprint· en· Decision Sciences
machine prediction:candidate · metaresearch+scholarly_communication+open_scienceconsensus · none
22
citations
fundno affunlabeled
NEWS
Elizabeth Wager, Sabine Kleinert
2013· review· fr· Journal of Global Health· Decision Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
19
citations
affgemma · metaresearchgpt · metaresearch+research_integrity+scholarly_communicationmodels split
Re-evaluation of solutions to the problem of unprofessionalism in peer review
Travis G. Gerwing, Alyssa M. Allen Gerwing, Chi‐Yeung Choi, Stephanie Avery‐Gomm, Jeff C. Clements, Joshua A. Rash
2021· article· en· Research Integrity and Peer Review· Decision Sciences
machine prediction:candidate · metaresearch+research_integrityconsensus · metaresearch
17
citations
affunlabeled
Google Scholar and Scopus
Sarah Bonato
2016· article· en· Journal of the Medical Library Association JMLA· Decision Sciences
machine prediction:candidate · bibliometrics+scholarly_communication+insufficient_payloadconsensus · none
17
citations
affunlabeled
Mastodon over Mammon: towards publicly owned scholarly knowledge
Björn Brembs, A. Lenardic, Peter Murray‐Rust, Leslie Chan, Dasapta Erwin Irawan
2023· review· en· Royal Society Open Science· Decision Sciences
machine prediction:candidate · scholarly_communication+open_scienceconsensus · none
14
citations
affunlabeled
Reproducibility of COVID-19 pre-prints
Annie Collins, Rohan Alexander
2022· article· en· Scientometrics· Decision Sciences
machine prediction:candidate · metaresearch+bibliometricsconsensus · none
14
citations
affunlabeled
Preprint Servers in Kidney Disease Research
Caitlyn Vlasschaert, Cameron Giles, Swapnil Hiremath, Matthew B. Lanktree
2020· review· en· Clinical Journal of the American Society of Nephrology· Decision Sciences
machine prediction:candidate · scholarly_communication+open_scienceconsensus · none
12
citations
affunlabeled
Impact of Transformative Agreements on Publication Patterns
Caitlin Bakker, Allison Langham-Putrow, Amy Riegelman
2024· article· en· International Journal of Librarianship· Decision Sciences
machine prediction:candidate · metaresearch+scholarly_communication+open_scienceconsensus · none
12
citations
afffundgemma · metaresearch+research_integrity+scholarly_communicationgpt · metaresearch+research_integrity+scholarly_communicationmodels agree
Lessons from the COVID-19 pandemic and recent developments on the communication of clinical trials, publishing practices, and research integrity: in conversation with Dr. David Moher
Daeria O. Lawson, Michael Ke Wang, Kevin Kim, Rachel Eikelboom, Myanca Rodrigues, Daniela Trapsa +2 more
2022· letter· en· Trials· Decision Sciences
machine prediction:candidate · metaresearch+research_integrityconsensus · metaresearch
11
citations
affunlabeled
The Level of Evidence Presented at Plastic Surgery Meetings
Jennifer E. Chuback, Talia L. Varley, Blake Yarascavitch, Felmont F. Eaves, Mohit Bhandari
2013· article· en· Plastic & Reconstructive Surgery· Decision Sciences
machine prediction:candidate · metaresearchconsensus · none
10
citations
afffundgemma · open_sciencegpt · scholarly_communication+open_sciencemodels split
Making science public: a review of journalists’ use of Open Science research
Alice Fleerackers, Natascha Chtena, Stephen Pinfield, Juan Pablo Alperín, Germana Barata, Monique Batista de Oliveira +1 more
2023· review· en· F1000Research· Decision Sciences
machine prediction:candidate · metaresearch+open_scienceconsensus · none
10
citations
affunlabeled
Google Scholar and Scopus
Sarah Bonato
2016· article· en· Journal of the Medical Library Association JMLA· Decision Sciences
machine prediction:candidate · metaresearch+bibliometrics+insufficient_payloadconsensus · none
10
citations
affunlabeled
Success Factors for Open Access
J. E. Till
2003· article· en· Journal of Medical Internet Research· Decision Sciences
machine prediction:candidate · metaresearch+open_scienceconsensus · none
9
citations

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