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O SciELO Data é um repositório multidisciplinar para depósito, preservação e disseminação de dados de pesquisa de artigos submetidos e aprovados para publicação, ou já publicados em periódicos da Rede SciELO, ou depositados no SciELO Preprints. Para mais informação consulte scielo.org.

Antes de realizar qualquer depósito, consulte os Termos e condições de uso do repositório SciELO Data.


SciELO Data es un repositorio multidisciplinario para depositar, preservar y difundir datos de investigación de artículos enviados, aprobados para publicación o ya publicados en revistas de la Red SciELO o depositados en SciELO Preprints. Para obtener más información, consulte scielo.org.

Antes de realizar cualquier depósito, consulte el Términos y condiciones de uso de SciELO Data.


SciELO Data is a multidisciplinary repository for deposition, preservation and dissemination of research data from articles submitted and approved for publication, already published in SciELO Network journals or deposited in SciELO Preprints. For more information visit scielo.org.

Before any deposit, consult the SciELO Data Terms and Conditions of Use.

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1,971 to 1,980 of 5,352 Results
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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