Hmmm. My conjecture/interpretation, when you pointed that out, was that the rating plotted out in the profile page is a weighted average, or interpolation, of the “low boundary of the 1σ-confidence interval” (the “humble rank”) and the current Glicko-2 rating estimate, and basically moves from 100% humble rank at the beginning to 100% Glicko-2, as a function of the deviation itself.
Since ratings are considered “accurate” when the deviation reaches 160, I would guess the parameter for this interpolation slides as a function of the interval [350,160].
Something like this:
(sigh, I wish this platform allowed for math equations)
(EDIT: I realized the formula simplifies to this 
)
In the above formula I’m assuming that the Deviation starts out at 350 like it’s displayed in the graphs.
But even if that formula is right, that doesn’t answer why the deviation is displayed as 4.9. (It being expressed as “11.9 ±4.9” doesn’t surprise me, after all it’s what they do in a lot of scientific research too, note down a simplified symmetrical uncertainty even though the uncertainty is usually not symmetrical, and this quantity we’re talking about is essentially entirely made up)
I’d say that the true provisional rating being 1150 wouldn’t make sense given the example I brought up above (losing three games and gaining rating each time).
Also, note that 1150=1500-350, whereas 11.9 != 6 +4.9.
My guess is that the deviation is being converted into a “rank-like” quantity through the use of the usual formula, which is log-based, so it ends up doing this weird effect of shrinking the deviation.
Well, this is a very technical thread, and also the main topic of this thread is actually to devise a test to verify once and for all if the current rating volatility is hurting the handicap system and the matchmaking.