Figure 3. Taking the mean of 17 classifications is ≥95% reproducible whilst applying either the median or mode is ≥90% accurate.

(A) Only calculating the mean of 17 classifications achieves an essential agreement ≥95% for reproducibility International Standards Organization, 2007, followed by the median and the mode. (B) Heatmaps of the consensus formed via the mean, median or mode after 14 days incubation. Only drug images from the Expert + AMyGDA dataset are included. (C) The essential agreement between a consensus dilution formed from 17 classifications using the median or mode and the consensus Expert +AMyGDA dilution both exceed the required 90% threshold International Standards Organization, 2007. (D) The heatmaps clearly show how the volunteer consensus dilution is likely to be the same or greater than the Expert + AMyGDA consensus.

Figure 3—figure supplement 1. Taking the mean of 17 classifications is ≥95% reproducible whilst none of the methods reach have an essential agreement for accuracy of ≥90% when using the Expert dataset.

(A) Only calculating the mean of 17 classifications achieves an essential agreement ≥95% for reproducibility International Standards Organization, 2007, followed by the median and then the mode. There is no specified threshold for exact agreement; the trend is reversed with the mode performing best, followed by the median and then the mean. (B) Heatmaps of the consensus formed via the mean, median, or mode after 14 days incubation. Each consensus dilution is a different selection, with replacement, of the original classifications. Drug images from the larger Expert dataset are included. (C) The essential agreement between a consensus dilution formed from 17 classifications using the median or mode and the consensus Expert dilution is ≥ 90%, which is the required threshold International Standards Organization, 2007. (D) The heatmaps clearly show how the volunteer consensus dilution is likely to be the same or greater than the Expert consensus.