{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T23:33:10Z","timestamp":1773099190223,"version":"3.50.1"},"reference-count":33,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002241","name":"Japan Science and Technology Agency (JST) Core Research for Evolutional Science and Technology (CREST), Japan","doi-asserted-by":"publisher","award":["JPMJCR21D4"],"award-info":[{"award-number":["JPMJCR21D4"]}],"id":[{"id":"10.13039\/501100002241","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/access.2023.3339548","type":"journal-article","created":{"date-parts":[[2023,12,5]],"date-time":"2023-12-05T18:25:42Z","timestamp":1701800742000},"page":"138870-138881","source":"Crossref","is-referenced-by-count":10,"title":["Dynamic Selection of Reliance Calibration Cues With AI Reliance Model"],"prefix":"10.1109","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7514-9040","authenticated-orcid":false,"given":"Yosuke","family":"Fukuchi","sequence":"first","affiliation":[{"name":"Digital Content and Media Sciences Research Division, National Institute of Informatics, Tokyo, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5907-7382","authenticated-orcid":false,"given":"Seiji","family":"Yamada","sequence":"additional","affiliation":[{"name":"Digital Content and Media Sciences Research Division, National Institute of Informatics, Tokyo, Japan"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2870052"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/s11747-019-00710-5"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1177\/0018720814547570"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1518\/001872097778543886"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/HRI.2016.7451740"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-07458-0_24"},{"issue":"44","key":"ref7","first-page":"3817","article-title":"Explanations that backfire: Explainable artificial intelligence can cause information overload","volume-title":"Proc. Annu. Meeting Cognit. Sci. Soc.","volume":"44","author":"Ferguson"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3173574.3174223"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3301275.3302316"},{"key":"ref10","first-page":"1","article-title":"Selectively providing reliance calibration cues with reliance prediction","volume-title":"Proc. Annu. Meeting Cognit. Sci. Soc.","volume":"45","author":"Fukuchi"},{"key":"ref11","first-page":"1","article-title":"Trust and reliance in XAI\u2014Distinguishing between attitudinal and behavioral measures","volume-title":"Proc. CHI Workshop Trust Reliance AI-Human Teams","author":"Scharowski"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3359616"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/2516540.2516554"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3025171.3025198"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1518\/001872006779166334"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0229132"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3042556"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.apergo.2017.07.006"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-39200-9_18"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.54941\/ahfe100971"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1017\/S0263574721000023"},{"key":"ref22","first-page":"1","article-title":"Attention is all you need","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Vaswani"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00191"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3176104"},{"key":"ref25","first-page":"1321","article-title":"On calibration of modern neural networks","volume-title":"Proc. 34th Int. Conf. Mach. Learn.","volume":"70","author":"Guo"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1136\/emermed-2017-206735"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3171221.3171258"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3319502.3374839"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-25554-5_57"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/HRI.2019.8673169"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3171221.3171275"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/IROS55552.2023.10341684"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.3758\/BRM.41.4.1149"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10005208\/10343151.pdf?arnumber=10343151","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T01:32:26Z","timestamp":1705023146000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10343151\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":33,"URL":"https:\/\/doi.org\/10.1109\/access.2023.3339548","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}