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Model-based ensembles: Lessons learned from retrospective analysis of COVID-19 infection forecasts across 10 countries.
Drews, Martin; Kumar, Pavan; Singh, Ram Kumar; De La Sen, Manuel; Singh, Sati Shankar; Pandey, Ajai Kumar; Kumar, Manoj; Rani, Meenu; Srivastava, Prashant Kumar.
Afiliação
  • Drews M; Department of Technology, Management and Economics, Technical University of Denmark, Kgs. Lyngby 2800, Denmark. Electronic address: mard@dtu.dk.
  • Kumar P; Rani Lakshmi Bai Central Agricultural University, Jhansi 284003, India. Electronic address: pawan2607@gmail.com.
  • Singh RK; Department of Natural Resources, TERI School of Advanced Studies, New Delhi 110070, India. Electronic address: singhramkumar@gmail.com.
  • De La Sen M; Institute of Research and Development of Processes IIDP, Department of Electricity and Electronics, University of the Basque Country, PO Box 48940, Leioa, Spain. Electronic address: manuel.delasen@ehu.eus.
  • Singh SS; Rani Lakshmi Bai Central Agricultural University, Jhansi 284003, India. Electronic address: directorextension.rlbcau@gmail.com.
  • Pandey AK; Rani Lakshmi Bai Central Agricultural University, Jhansi 284003, India. Electronic address: pandey.ajai1@gmail.com.
  • Kumar M; Forest Research Institute, Dehradun, Uttarakhand 248006, India. Electronic address: manojfri@gmail.com.
  • Rani M; Department of Geography, Kumaun University, Nainital, Uttarakhand 263001, India. Electronic address: meenurani06@gmail.com.
  • Srivastava PK; Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi 221005, India. Electronic address: prashant.just@gmail.com.
Sci Total Environ ; 806(Pt 2): 150639, 2022 Feb 01.
Article em En | MEDLINE | ID: mdl-34592277
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article
Texto completo
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article