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MS Word - 26.6 KB - MD5: 7189c19993110535f40f39e416e47850
Sep 19, 2023 - Revista Direito GV
Wang, Daniel Wei Liang; Arruda, Ana Luiza Gajardoni de Mattos; Oliveira, Bruno da Cunha de; Santos, Ezequiel Fajreldines dos; Moribe, Gabriela Tiemi; Pedro, Marcela Pereira; Heck, Leonardo Nochang; Esteves, Luiz Fernando Gomes, 2023, "Data for: STF and public measures for COVID-19 prevention and treatment", https://doi.org/10.48331/scielodata.1FPGX2, SciELO Data, V1, UNF:6:J9SxSQNvUjd5qQp7CDR33Q== [fileUNF]
English: This article analyses the case-law of the Brazilian Supreme Federal Court (STF) in relation to the policies for the prevention and treatment of Covid-19. With the support of data science and artificial intelligence, the STF´s decisions were systematically and exhaustivel...
Plain Text - 4.5 KB - MD5: 090c919973ecb2e7ff06d9622ff471b9
README file that explains the dataset.
Tabular Data - 17.9 KB - 1 Variables, 253 Observations - UNF:6:J9SxSQNvUjd5qQp7CDR33Q==
Dataset.
Sep 18, 2023 - Ciência & Saúde Coletiva
Mattos, Maurício; Gutiérrez, Adriana, 2023, "Data for: Novas conformações do apoio matricial em tempos de pandemia de Covid-19", https://doi.org/10.48331/scielodata.HGB1NA, SciELO Data, V1
Arquivos referentes ao artigo "Novas conformações do apoio matricial em tempos de pandemia de Covid-19". Tabela com os dados extraídos do websurvey aplicado aos trabalhadores do NASF de Maricá.
MS Excel Spreadsheet - 15.7 KB - MD5: f612464e44375b4a23b5b0075dde1a41
Dados extraídos do websurvey aplicado junto aos profissionais da equipe NASF.
MS Word - 12.4 KB - MD5: 9db936116dd7eb703ae5db5e4850566e
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