Fig.5.

The “Einstein-from-noise” pitfall. (A) Class averages for the 15 largest classes (ordered from larger to smaller) after sorting and 2D class averaging of the auto-picked particles that were picked with a threshold of 0.1. Class averages indicated with an asteriks were identified as artificial classes caused by template bias (see Section 5). (B) Examples of particle images assigned to one of the artificial classes: the third class in A. No clear particles are visible. The lower-right image shows the average of all assigned particles in this class without any CTF correction. (C) Examples of particle images assigned to a good class: the first class in A. Particles are clearly visible. The lower-right image shows the average of all assigned particles in this class without any CTF correction. (D) 3D map obtained from 17,082 particles that were assigned to artificial classes.