Academic Thesis

Basic information

Name Tanemura Nanae
Belonging department
Occupation name
researchmap researcher code 7000025167
researchmap agency

Title 

Feature extraction contributing to risk-acceptance prediction by machine learning models in food benefit-risk communication in Japan

					

					

						

							

								

									
OwnerRoles 

									
								

							

						

						
 

					

					

						

							

								

									
Author 

									
								

							

						

						
Nanae Tanemura
Yusuke Machii
Masako Kakizaki
Takashi Kusumi
Rie Onodera
Yoshiko Tominaga
Michihiro Araki

					

					

						

							

								

									
Summary 

									
								

							

						

						
 

					

					

						

							

								

									
Magazine(name) 

									
								

							

						

						
Food and Humanity

					

					

						

							

								

									
Publisher 

									
								

							

						

						
Elsevier BV

					

					

						

							

								

									
Volume 

									
								

							

						

						
3

					

					

						

							

								

									
Number Of Pages 

									
								

							

						

						
 

					

					

						

							

								

									
StartingPage 

									
								

							

						

						
100427

					

					

						

							

								

									
EndingPage 

									
								

							

						

						
100427

					

					

						

							

								

									
Date of Issue 

									
								

							

						

						
2024-12

					

					

						

							

								

									
Referee 

									
								

							

						

						
true

					

					

						

							

								

									
Invited 

									
								

							

						

						
 

					

					

						

							

								

									
Language 

									
								

							

						

						
 

					

					

						

							

								

									
Thesis　Type 

									
								

							

						

						
Research papers (academic journals)

					

					

						

							

								

									
International Journal 

									
								

							

						

						
true

					

					

						

							

								

									
International Collaboration 

									
								

							

						

						
false

					

					

						

							

								

									
ISSN 

									
								

							

						

						
 

					

					

						

							

								

									
eISSN 

									
								

							

						

						
 

					

					

						

							

								

									
ISBN 

									
								

							

						

						
 

					

					

						

							

								

									
DOI 

									
								

							

						

						
10.1016/j.foohum.2024.100427

					

					

						

							

								

									
NAID 

									
								

							

						

						
 

					

					

						

							

								

									
Cinii Books Id 

									
								

							

						

						
 

					

					
					

						

							

								

									
PMID 

									
								

							

						

						
 

					

					

						

							

								

									
PMCID 

									
								

							

						

						
 

					

					
					

						

							

								

									
Format 

									
								

							

						

						
Doi

					

					

						

							

								

									
Download 

									
								

							

						

						
false

					

					

						

							

								

									
J-GLOBAL ID 

									
								

							

						

						
 

					

					

						

							

								

									
arXiv ID 

									
								

							

						

						
 

					

					

						

							

								

									
ORCID Put Code 

									
								

							

						

						
 

					

					

						

							

								

									
DBLP ID 

									
								

							

						

						
 

					

					

						

							

								

									
Major Achivement 

									
								

							

						

						
false