[kevinlenane]

For sure nothing is totally "perfect" when it comes to grading - the concern about the machine learning viral error idea - isn't exactly how it works. We actually have 3 distinct human inputs and several more classes of machine inputs all providing grades on the same sample cards so in theory over time any nuance gets built in to the best average grade per category. We are planning on having the proof of concept ready to grade several vintage wax breaks live on camera for the Beckett Industry Summit - and ill fire out the test version here if folks want to give feedback on it technically (technically meaning as it relates to the grade evaluation not coding). I want to incorporate as much feedback as possible amongst the group here for the vintage grading in particular as there is a lot of nuance to various set/year pairs that I feel should be included over time. My goal here is to provide an instant service that is transparent provides all the available raw data that make up and produce the various numbers.