> Personally, I expect more rigor from any analysis and would hold myself to a higher standard.

When something is "pretty bizarre" the most likely conclusion is "I fucked up", which is very likely in this case. I really wonder if he actually checked the results of the classifier. These things can be wildly inaccurate since differences in languages can be quite small at times and some are very human language oriented. He even admits that Java and Kotlin should be higher but then doesn't question Perl, R, Applescript, Rust, and the big drop to Python. What's the joke? If you slam your head on the keyboard you'll generate a valid Perl program?

It worries me that I get this feeling from quite a number of ML people who are being hired and paid big bucks from big tech companies. I say this as someone in ML too. There's a propensity to just accept outputs rather than question them. This is like a basic part of doing any research, you should always be incredibly suspicious of your own results. What did Feynman say? Something like "The first rule is not to be fooled and you're the easiest person to fool"?