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Artigo de periodico
Evaluation of the amazon river seasonal influences on glycerophospholipids in wild fish (2024)
Correia, Banny S. B; Pontes, Joao Guilherme M; Torrinhas, Raquel Susana Matos de Miranda ; Val, Adalberto Luis; Thomas, Christopher Paul; Tasic, Ljubica
Source: Journal of the brazilian chemical society. Unidade: FM
Subjects: PEIXES, ÁCIDOS GRAXOS, ESPECTROMETRIA DE MASSAS, FÍGADO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CORREIA, Banny S. B et al. Evaluation of the amazon river seasonal influences on glycerophospholipids in wild fish. Journal of the brazilian chemical society, v. 35, n. 7, 2024Tradução . . Disponível em: https://observatorio.fm.usp.br/handle/OPI/76929. Acesso em: 27 jan. 2026.
APA
Correia, B. S. B., Pontes, J. G. M., Torrinhas, R. S. M. de M., Val, A. L., Thomas, C. P., & Tasic, L. (2024). Evaluation of the amazon river seasonal influences on glycerophospholipids in wild fish. Journal of the brazilian chemical society, 35( 7). doi:10.21577/0103-5053.20240015
NLM
Correia BSB, Pontes JGM, Torrinhas RSM de M, Val AL, Thomas CP, Tasic L. Evaluation of the amazon river seasonal influences on glycerophospholipids in wild fish [Internet]. Journal of the brazilian chemical society. 2024 ; 35( 7):[citado 2026 jan. 27 ] Available from: https://observatorio.fm.usp.br/handle/OPI/76929
Vancouver
Correia BSB, Pontes JGM, Torrinhas RSM de M, Val AL, Thomas CP, Tasic L. Evaluation of the amazon river seasonal influences on glycerophospholipids in wild fish [Internet]. Journal of the brazilian chemical society. 2024 ; 35( 7):[citado 2026 jan. 27 ] Available from: https://observatorio.fm.usp.br/handle/OPI/76929
Artigo de periodico
Improving the training performance of generative adversarial networks with limited data: Application to the generation of geological models (2024)
Ranazzi, Paulo Henrique; Xiaodong, Luo ; Pinto, Marcio Augusto Sampaio
Source: Computers & Geosciences. Unidade: EP
Assunto: REDES E COMUNICAÇÃO DE DADOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RANAZZI, Paulo Henrique e XIAODONG, Luo e PINTO, Marcio Augusto Sampaio. Improving the training performance of generative adversarial networks with limited data: Application to the generation of geological models. Computers & Geosciences, v. no 2024, p. 13 , 2024Tradução . . Disponível em: https://doi.org/10.1016/j.cageo.2024.105747. Acesso em: 27 jan. 2026.
APA
Ranazzi, P. H., Xiaodong, L., & Pinto, M. A. S. (2024). Improving the training performance of generative adversarial networks with limited data: Application to the generation of geological models. Computers & Geosciences, no 2024, 13 . doi:10.1016/j.cageo.2024.105747
NLM
Ranazzi PH, Xiaodong L, Pinto MAS. Improving the training performance of generative adversarial networks with limited data: Application to the generation of geological models [Internet]. Computers & Geosciences. 2024 ; no 2024 13 .[citado 2026 jan. 27 ] Available from: https://doi.org/10.1016/j.cageo.2024.105747
Vancouver
Ranazzi PH, Xiaodong L, Pinto MAS. Improving the training performance of generative adversarial networks with limited data: Application to the generation of geological models [Internet]. Computers & Geosciences. 2024 ; no 2024 13 .[citado 2026 jan. 27 ] Available from: https://doi.org/10.1016/j.cageo.2024.105747

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