To estimate the rate of false positive spectra in the dataset and evaluate the QSRR model performance, 600 randomly selected spectra were visually assessed and included into a reviewed external set (RE set). During the assessment, we checked if a single chromatographic peak was assigned to the target molecule. We also analysed if the ions detected during the chromatographic peak matched probable molecule fragments. 17 spectra did not include a chromatographic peak at all and were defined as "BAD", or false positive datapoints. 18 spectra contained incorrectly assigned peak and were labeled as "WRONG RT". The mean RT assignment error was 8.64 s, or 7% of the method duration (median -4.49 s, or 3.7%; standard deviation -9.79 s). Other 565 spectra contained a single molecular peak and were marked as "GOOD". Thus, we consider that the error rate of the whole dataset can be estimated as 5.8%, which makes the reviewed external set a crucial tool for proper model performance estimation. The rest of the dataset was divided deliberately into the training set (523,578 points) and the crude external set (CE set, 57,508 points).