R lme4 interpret MLM confidence intervals I'm using the lme4 package in R to run a multilevel model and to calculate confidence intervals:
model <- lmer(cadence ~ fd + height + (1+fd|id), data=df, REML=F)

confint.merMod(model, method = "boot", boot.type = "perc", nsim = 500, oldNames = F)

I'm trying to understand what the output is showing me:
                             2.5 %      97.5 %
sd_(Intercept)|id      0.590230649  0.92396467
cor_fd.(Intercept)|id -0.999990953  1.00000000
sd_fd|id               0.003862849  0.10373958
sigma                  0.295910811  0.35343478
(Intercept)           -0.247134271  0.27844609
fd                    -0.038814987  0.04487689
height                -0.795405634 -0.28511542

The fd and height rows are showing my the .95CI around the respective regression coefficient (fixed effects)
The ones I'm mainly struggling with are sd_(Intercept)|id, cor_fd.(Intercept)|id, and sd_fd|id. What do they represent?
My best guess is that sd_(Intercept)|id is the CI around the standard deviation of intercept values. If so, then what does sigma represent?
sd_fd|id Im guessing is the SD of all the estimated slope values for each id
Finally, I'm not sure what cor_fd.(Intercept)|id is meant to show?
 A: Here I fit an example model using the built-in sleepstudy dataset.  
(fm1 <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy))
#Linear mixed model fit by REML ['lmerMod']
#Formula: Reaction ~ Days + (Days | Subject)
#   Data: sleepstudy
#REML criterion at convergence: 1743.628
#Random effects:
# Groups   Name        Std.Dev. Corr
# Subject  (Intercept) 24.740       
#          Days         5.922   0.07
# Residual             25.592       
#Number of obs: 180, groups:  Subject, 18
#Fixed Effects:
#(Intercept)         Days  
#     251.41        10.47  

These are the confidence intervals (on the right, I list what each interval pertains to):  
confint.merMod(fm1, method = "boot", boot.type = "perc", nsim = 500, oldNames = F)
#Computing bootstrap confidence intervals ...
#                                   2.5 %      97.5 %
#sd_(Intercept)|Subject        13.1760846  35.3154169 --> random intercept SD
#cor_Days.(Intercept)|Subject  -0.5739618   0.9384943 --> correlation between random intercept and random slope
#sd_Days|Subject                3.2990883   8.1234449 --> random slope SD
#sigma                         22.6901363  28.3167813 --> residual SD
#(Intercept)                  237.9993456 265.4882890 --> fixed intercept
#Days                           7.1383003  13.6773242 --> fixed slope

