Nevertheless, the aforementioned non-linear relationship did not hinder easy visual identification of the outliers, i.e. compounds for which our predicted and experimental RT values do not correlate. In Figure , these outliers are shown by black ellipses. We selected 10 compounds corresponding to 5 outliers and 5 datapoints consistent with the prediction from the OL set (Table ). Then, we performed at least two LC-MS experiments for each compound using a method as close as possible to that used for METLIN SMRT. The main difference between the two experiments was the dwell volume, which was 900 L for METLIN SMRT and 420 L in our experiments, thus reducing our experimental RT values by ca. 288 s. For both compounds where the METLIN RT value was lower than that predicted by our model, our LC-MS experiment gave a much higher RT value. The same happened for the opposite case of outliers -our re-measured RT value was much closer to the predicted one. The two out of three data points that not retained according to METLIN SMRT dataset also did not retain in our experiment, but one that was expected to be retained had RT = 377.3 s (or 665.3 s with the 288-s difference added). Finally, the difference between RT values obtained in our experiments and those reported in METLIN SMRT for the data points that had "good" prediction according to our model was small. These results show that in all 10 cases re-evaluated by us experimentally, high prediction errors likely originated from inconsistencies in the original METLIN SMRT dataset and not prediction model issues.