title: Assessing Confidence in Predictions Using Veracity and Utility - A Case Study on the Prediction of Mammalian Metabolism by Meteor Nexus.
abstract: A previous paper1 described new metrics, veracity and utility, for assessing the performance of toxicity prediction systems that report confidence in their predictions. Assessing the performance of systems that predict mammalian metabolism is complicated by the absence of comprehensive sets of negative observations and predictions. This paper presents an approach to assessing the performance of such systems using veracity and utility.
authors.affiliation: Heather Lea, Bland Hill, Norwood, Harrogate HG3 1TE, UK phone: +44(0)1843880241. philip.judson@blubberhouses.net.
authors.forename: Philip N
authors.initials: PN
authors.lastname: Judson
authors.affiliation: Lhasa Limited, Granary Wharf House, 2 Canal Wharf, Leeds LS11 5PS, UK.
authors.forename: Anthony
authors.initials: A
authors.lastname: Long
authors.affiliation: Lhasa Limited, Granary Wharf House, 2 Canal Wharf, Leeds LS11 5PS, UK.
authors.forename: Ernest
authors.initials: E
authors.lastname: Murray
authors.affiliation: Lhasa Limited, Granary Wharf House, 2 Canal Wharf, Leeds LS11 5PS, UK.
authors.forename: Mukesh
authors.initials: M
authors.lastname: Patel
mesh_terms: D006801:Humans; D055442:Metabolome / Q000502:physiology*; D008954:Models, Biological
keywords: Computational chemistry; Metabolism; Performance assessment; Prediction models