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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.

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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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Regional Development and Management Studies
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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.

176 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.
176 works in the cohort · of 4,299,418page 1 of 4

Labels cover 0 of 176 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 176 of 176 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.

affaboutunlabeled
Abattoirs, Meat Processing and Managerial Challenges
Sylvain Charlebois, Amit Summan
2014· article· en· International Journal of Rural Management· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
18
citations
aboutno affunlabeled
Sustainable development in the context of the Olympic Games.
B. M. Monica, M. Sabina, Meisa Sofia
2015· article· en· Ovidius University Annals, Physical Education and Sport/Science, Movement and Health Series· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
6
citations
aboutno affunlabeled
Emigracioni potencijal mladih u Srbiji
Milica Todorović, Vanja Javor, Nevena Radić
2020· article· en· Migracijske i etničke teme / Migration and Ethnic Themes· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
5
citations
venueno affunlabeled
Investment Activity in Small Open Economies
Vera Karadjova, Snežana Dičevska
2014· article· en· Technology and Investment· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
3
citations
aboutno affunlabeled
Evolution of GDP and Foreign Investments
Constantin Anghelache, Gabriela Victoria Anghelache, Mădălina-Gabriela Anghel, Adina Mihaela Dinu
2013· article· en· Romanian Statistical Review Supplement· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
3
citations
fundno affunlabeled
Managing Protected Areas
Niall Finneran, Denise Hewlett, Richard Clarke
2023· book· en· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
2
citations
aboutno affunlabeled
MILK PRODUCTION IN SERBIA AND POSITION SMALL FARMERS
Božo Drašković, Zoran Rajković, Dusan Kostic
2010· article· en· AgEcon Search (University of Minnesota, USA)· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Ispitivanja skala COMPIN-10 i SUCOMP-10
Đorđe Čekrlija, Julie Aitken Schermer, Ivan Zečević, Ilija Dojchinovski, Nikola Rokvić, Yamen Hrekes +5 more
2025· article· en· Psihologijske teme· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
1
citations
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