Shaddows - 3:41 pm on Jun 9, 2011 (gmt 0)
Think of it in 3 stages.
1) Definition of criteria that is being considered. This consitutes the Panda version. It is defined by engineers. Example: Keyword density (AFAIK, KW density is NOT a Panda factor)
2) Current "Understanding" of criteria. This is machine learnt, iteratively. There are several iterations between version updates. It is defined by seed sets, and refined by world data. Example "Optimum KWD = 12%, ranking points allocated on a power curve" (12% is NOT a good KWD, and a power curve is NOT a good distribution curve for this data)
3) Application to crawl data. This is updated on the fly like regular data. Example "This site has a KWD of 15%, so gets 10 points"
Edit for clarification