Figure: something having to do with robustness (?)

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in the beginning part of the run, you see an accumulation of coding sites which means that your robustness is going down; gene duplications causing direct task acquisition, but in the last few tasks it seems a lot more like fine tuning; is this a bi-phasic process where the second part the more traditional duplication and divergence and the extra material; and there is selection for simplicity with the number of coding sites going down

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Need to check for sign mistake or other bug: the coding site deltas from having zero tasks to having >=1 task should only be positive. Right now, they are all zero for the slip insertion mask being False and there are only three nonzero for the slip duplicate being true

[mmore500]

Possible interpretation: the num tasks has is the number of tasks that you end up with, not the number that you start out with

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Try tweaking this to not double count the same site over multiple tasks

df = df.with_columns(
    pl.col("Is Task Coding Site Delta").sum().over(
        ["Treatment", "Run ID", "Generation Born"],
    )
    .alias("is task coding site delta sum"),
)

[mmore500]

Are the slip mutations increasing coding sites for large number of tasks due to them causing gain of entirely new tasks?

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• [x] todo look at median
• [ ] fix axis labels to be proper English, not raw column names