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@@ -5,9 +5,11 @@ author: - David Vorgrimmler^1^ - Denis Gebele^1^ - Martin Gütlein^2^ - - Benoit Schilter^3^ - - Elena Lo Piparo^3^ -include-before: ^1^ in silico toxicology gmbh, Basel, Switzerland\newline^2^ Inst. f. Computer Science, Johannes Gutenberg Universität Mainz, Germany\newline^3^ Chemical Food Safety Group, Nestlé Research Center, Lausanne, Switzerland + - Barbara Engeli^3^ + - Jürg Zarn^3^ + - Benoit Schilter^4^ + - Elena Lo Piparo^4^ +include-before: ^1^ in silico toxicology gmbh, Basel, Switzerland\newline^2^ Inst. f. Computer Science, Johannes Gutenberg Universität Mainz, Germany\newline^3^ Federal Food Safety and Veterinary Office (FSVO) , Risk Assessment Division , Bern , Switzerland\newline^4^ Chemical Food Safety Group, Nestlé Research Center, Lausanne, Switzerland keywords: (Q)SAR, read-across, LOAEL, experimental variability date: \today abstract: | @@ -487,7 +489,7 @@ The combined test set has a mean standard deviation (-log10 transformed values) `r round(mean(10^(-1*c.dup$sd)),2)` mmol/kg_bw/day) ([@fig:intra]). -![Distribution and variability of compounds with multiple LOAEL values in both databases Each vertical line represents a compound, dots are individual LOAEL values.](figures/dataset-variability.pdf){#fig:intra} +![LOAEL distribution and variability of compounds with multiple measurements in both databases. Compounds were sorted according to LOAEL values. Each vertical line represents a compound, and each dot an individual LOAEL value. Experimental variability can be inferred from dots (LOAELs) lying on the same line (compound).](figures/dataset-variability.pdf){#fig:intra} ##### Inter database variability |