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I usually prefer to get as much learn data captured before, performing a transfer. It's already part of the gross fuel table. I'll run one or two iterations and manually clean up the fuel map (peaks/valleys). As indicated above, your cam may or may not like low speed learn or closed loop for that matter, you'll need to verify if the data is valid. There are some cool features of the datalogger using the scatter plot that show how well areas of your run are mapped.
 

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Say hypothetically that I may have clicked yes. Hypothetically of course, what's the problem?
I've used the smoothing function many times, it works well when you have a lot of learn correction. When you have small amounts of correction, it can get washed out, same with improperly setup axis and learning interpolation. Leave the learn data alone for a bit, until you have found target AFR's that the engine likes at various levels of load and RPM. Once you have those dialed in, you can begin to shape your fuel curve. Realistically, you can transfer learning to base only twice, once for the rough curve, perform some manual smoothing and cleanup and run that file for a bit to see if there's any final cleanup that needs to be done. When all finished, go in shut off the learning and tighten up the closed loop correction limits.
 
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