{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T17:45:07Z","timestamp":1778694307825,"version":"3.51.4"},"reference-count":22,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Instrum. Meas. Mag."],"published-print":{"date-parts":[[2021,4]]},"DOI":"10.1109\/mim.2021.9400955","type":"journal-article","created":{"date-parts":[[2021,4,12]],"date-time":"2021-04-12T20:47:06Z","timestamp":1618260426000},"page":"84-92","source":"Crossref","is-referenced-by-count":54,"title":["Machine Learning in Measurement Part 1: Error Contribution and Terminology Confusion"],"prefix":"10.1109","volume":"24","author":[{"given":"Shervin","family":"Shirmohammadi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hussein","family":"Al Osman","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2020.2987943"},{"key":"ref11","year":"2012","journal-title":"International vocabulary of metrology - Basic and general concepts and associated terms (VIM) BIPM"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.physrep.2019.03.001"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/MIM.2021.9345597"},{"key":"ref14","year":"2008","journal-title":"Evaluation of Measurement Data - Guide to the Expression of Uncertainty in Measurement (GUM 1995 with minor corrections) Joint Committee for Guides in Metrology"},{"key":"ref15","year":"1994","journal-title":"Accuracy (Trueness and Precision) of Measurement Methods and Results&#x2014;Part 1 General Principles and Definitions"},{"key":"ref16","author":"han","year":"2000","journal-title":"Data Mining Concepts and Techniques"},{"key":"ref17","first-page":"332","article-title":"Precision and recall for regression","volume":"5808","author":"torgo","year":"2009","journal-title":"Proc Discovery Science 12th Int Conf (DS"},{"key":"ref18","first-page":"1050","article-title":"Dropout as a Bayesian approximation: representing model uncertainty in deep learning","author":"gal","year":"0","journal-title":"Proc Int Conf Conf Mach Learn"},{"key":"ref19","first-page":"4907","article-title":"Bayesian uncertainty estimation for batch normalized deep networks","author":"teye","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref4","year":"2001","journal-title":"International Electrotechnical Vocabulary (IEV) - Part 300 Electrical and Electronic Measurements and Measuring Instruments"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/MIM.2020.9082796"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6501\/ab4b39"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/MIM.2016.7384954"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/MIM.2014.6825388"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/5289.887453"},{"key":"ref2","doi-asserted-by":"crossref","DOI":"10.1109\/MIM.2021.9436102","article-title":"Machine learning in measurement, part 2: uncertainty quantification","volume":"24","author":"al osman","year":"2021","journal-title":"IEEE Instrum Meas Mag"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/MIM.2020.9200875"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2014.2303533"},{"key":"ref20","first-page":"5580","article-title":"What uncertainties do we need in Bayesian deep learning for computer vision?","author":"kendall","year":"0","journal-title":"Proc 31st Int Conf Neural Information Processing Sys (NIPS 2017)"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1002\/9781119021315.ch7"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2020.2967877"}],"container-title":["IEEE Instrumentation &amp; Measurement Magazine"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5289\/9400949\/09400955.pdf?arnumber=9400955","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,11]],"date-time":"2023-09-11T18:09:58Z","timestamp":1694455798000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9400955\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4]]},"references-count":22,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/mim.2021.9400955","relation":{},"ISSN":["1094-6969","1941-0123"],"issn-type":[{"value":"1094-6969","type":"print"},{"value":"1941-0123","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,4]]}}}