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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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COVID-19 Pandemic Impacts
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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.

affaffiliation
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venuejournal
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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.

1,869 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.
1,869 works in the cohort · of 4,299,418page 34 of 38

Labels cover 10 of 1,869 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 1,869 of 1,869 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
Dataset of Policy Responses to COVID-19 pandemic in Vietnam
Tuyet Anh T. Le, Kelly Vodden, Jianghua Wu, Ghada Atiwesh
2020· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Impact of COVID-19 on Stock Markets: An Investigation and Way Forward
Aaditya Trivedi, Tajinder P. Singh, Kaushal Kishore
2021· article· en· International review of business and economics/International review of business and economics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Study of Factors Associated with the Rate of COVID-19 Infection
Yaraporn Sungkasing, Thanut Khaopong, Napatson Borrisutsuksri, Kawinpop Jularee, Sirisopa Amornsin, Phutawan Phuseeorn
2023· article· en· Global Journal of Health Science· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
A STUDY OF COVID-19 ON INDIAN ECONOMY
Mohit Fogaat, Sangeetha Sharma, Rajendra Prasad Meena
2022· article· en· GLOBAL JOURNAL FOR RESEARCH ANALYSIS· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Habits of Food Consumers in the Post COVID Era
María Aránzazu Sulé Alonso, Tea Rushit, Elvira Delgado-Márquez
2021· article· en· International Journal of Marketing Studies· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
The Impact of COVID-19 on the Austrian PFM System
Johann Seiwald, Tobias; id_orcid 0000-0001-5235-3412 Polzer
2020· article· en· WU Research· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Dataset of Policy Responses to COVID-19 pandemic in Vietnam
Tuyet Anh T. Le, Kelly Vodden, Jianghua Wu, Ghada Atiwesh
2020· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affvenueunlabeled
How to use a mask
Mengzhu Fu
2021· article· en· New Sociology Journal of Critical Praxis· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
COVID- 19 and Changes in Household Food Practices
Jacinthe Cloutier, Marie-Claude Roy, Amanda L. Roy
2021· article· en· Journal of Family & Consumer Sciences· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations

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