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tokens: cent confidence limits, respectively, analogous to 1σ and 2σ random experimental error bars. 2.1 The misinterpretation of the mass-error correlation The next step taken by K20 is to take the upper error bars on each MC trial’s measured M hi (i.e. the upper error bars on the data points in their fig. 3, or our Fig. 1 ), and plot them as a function of ( M hi − M hi,in ) (shown in their fig. 5). K20 name this latter quantity ‘overestimate of M hi ’, but which is equivalent to ‘ M hi /M − 18’, i.e. the difference between the output and input values of M hi . K20 observed that these two quantities are correlated, and interpreted this correlation as each randomly scattered data point being aware of how far it is from the centroid of the input distribution, and that this information is communicated back to the observer through the data point’s error bar. Continuing with this line of reasoning, K20 then claim that it is possible to transpose the results of each individual MC trial back to the input value of M hi,in with a precision of ±0.8 M. Finally, K20 then treats the analysis of the real-world sample of 24 progenitor mass estimates as though it were a single MC trial, and concludes that the best fit of M hi M should be adjusted down to M hi = 15.8 ± 0.8 M. This reduction of M hi , as well as its upper error bar, implies that the difference between M hi and the mass associated with the H–D limit is now in excess of 10σ, leading K20 to state that ‘the RSG problem remains’. In Figs 2 and 3 , we use the results of our MC experiment to make similar figures to fig. 5 in K20 , again seeing a correlation. However, in Fig. 2 , we make the same plot but for three different values of M hi,in . Were the individual data points aware of of the true input value of M hi,in , the three sets of data would be offset in the y -direction, since a different correction factor would be required for each different value of M hi,in . However, the exact same trend is seen irrespective of M hi,in . Hence, we can say that the trend seen in fig. 5 in K20 has no dependence on M hi,in . Figure 2. Our version of fig. 5 in K20 , showing the quantity ( M hi − 18 M) for each of our MC trials, as a function of the positive error bar on M hi for that trial. In addition to showing the results for the same input value as K20 ( M hi,in = 18 M), we also show the results for M hi,in = 20 and 22 M. The exact same trend is seen irrespective of M hi,in , demonstrating that the correlation seen in the plot does not depend on the input value of M hi . Figure 3. Same as our Fig. 2 , but for fixed M hi,in = 18 M, and with three different sizes of error bars on the input progenitor masses (σ M = 10, 20, and 30 per cent). Different trends are seen for each value of σ M , demonstrating that the correlation seen in fig. 5 of K20 is in fact caused by simple error propagation. Next, in Fig. 3 , we again recreate fig. 5 of K20 , but for MC experiments with fixed M hi,in = 18 M and three different values