“…Many models exist to predict specific gas chromatographic retention parameters such as retention index [1,3] or relative retention [4,5] for 1D GC separations. These models can be grouped into several different varieties, such as quantitative structure retention or property relationships (QS-RRs or QSPRs) [6][7][8][9][10][11][12][13], additive models [14,15], and boilingpoint-to-retention-time correlations [16][17][18][19][20]. Kovats retention indices and linear temperature-programed retention indices (LTPRI) are the most popular retention metrics to model [21].…”