{"version.version":"0.0.7","version.cm_url":"https://github.com/ceurws/ceur-spt","spt.html_url":"/Vol-4132/short53.html","spt.description":null,"spt.id":"Vol-4132/short53","spt.wikidataid":null,"spt.title":"An Entropic Metric for Measuring Calibration of Machine Learning Models","spt.pdfUrl":"https://ceur-ws.org/Vol-4132/short53.pdf","spt.volume":{"number":4132,"acronym":"TRUST-AI 2025","wikidataid":null,"title":"Proceedings of TRUST-AI 2025 - The European Workshop on Trustworthy AI","description":null,"url":null,"date":"2025-12-16","dblp":null,"k10plus":null,"urn":null},"spt.session":null,"cvb.id":"Vol-4132/short53","cvb.title":"An Entropic Metric for Measuring Calibration of Machine Learning Models","cvb.type":null,"cvb.position":null,"cvb.pagesFrom":null,"cvb.pagesTo":null,"cvb.authors":"Daniel James Sumler,Lee Devlin,Simon Maskell,Richard Oliver Lane","cvb.vol_number":"4132","cvb.pdf_name":"short53.pdf","cvb.pages":"169-179","cvb.fail":null}