provides close to a 1:1 ratio only at ee values of greater than 50% ee (Figure ). The relevant comparison of the two models is between racemic systems, and under these conditions, this ratio approaches 20,000:1 in the monomer-active model proposed in Ref. 41, as shown in Figure , which is four orders of magnitude greater than the experimentally confirmed value. If this monomer-active model were indeed operative, one would expect to observe a single 1 H-NMR peak, that for the heterochiral species, which is predicted to dominate under racemic conditions, instead of the two nearly equal peaks experimentally observed, as was shown in Figure . From Given these large discrepancies between the results of the purely computational monomer-active model of Ref. 41 and the overwhelming preponderance of the kinetic and spectroscopic experimental data, it is instructive to probe how such glaring inconsistencies could come about. First, the experimental data in the reaction profile of Figure used in their modeling derives from that of a reaction in which no product was added at the outset, which means that the kinetic model attempts to simulate simultaneously both the process of initial symmetry breaking and that of the subsequent chiral amplification. Deterministic kinetic modeling, such as that employed in Ref. 41, is unable to account for symmetry breaking in the absence of an initial imbalance. How, then, can the model results of Ref. 41 be explained? The answer can be found by scrutinizing the values of the kinetic parameters returned by the model and the implications for relative concentrations of species: although monomers are active as catalysts, the model shows that the system is driven overwhelmingly towards formation of the dimer reservoir so that the concentration of monomers is exceedingly low. For the first 450 minutes of the simulation shown in Figure , the total concentration of monomers R+S was ca. 5 ppm, or less than 0.025% of the total. Even more tellingly, the concentration difference between R and S monomers, which ultimately determines ee, was one in ten million. Such a small absolute difference in concentrations causes instability in the simulation because this difference approaches the level of round-off error of the computer used to carry out the simulation. Thus the force for symmetry breaking used in the computer model of the lab-based experimental reaction data arose from computational fluctuations in concentrations due to computer roundoff error. While such an approach may be a useful way to gain theoretical insight into general features caused by instabilities and fluctuations, it is difficult to make a case, as the authors do, 37b that the particular features of a particular computer modeling program can offer chemical insight into the experimental reaction under study in the laboratory.