[R] which coefficients for a gam(mgcv) model equation?

[doon75]

Dear users,
I am trying to show the equation (including coefficients from the model
estimates) for a gam model but do not understand how to.
Slide 7 from one of the authors presentations (gam-theory.pdf  URL: 
http://people.bath.ac.uk/sw283/mgcv/) shows a general equation
log{E(yi )} = α+ ßxi + f (zi ) .
What I would like to do is put my model coefficients and present the
equation used. I am an ecologist not a statistician - and have no access to
statistical advice.
How would I use values from the model below to complete the equation: 
log{E(yi )} = α+ ßxi + f (zi )?
Many thanks,
Darren

## from the help
library(mgcv)
set.seed(0) ## simulate some data...
dat <- gamSim(1,n=400,dist="normal",scale=2)
b<-gam(y~s(x0)+s(x1)+s(x2)+s(x3),data=dat)
summary(b)

 I have tried searching help forum with "gam equation" I was not able to
find an answer from the 18 threads returned.
Also tried looking at "?predict.gam" and simply "predict.gam" however my
understanding of R is not sufficient to understand the details to be able to
answer my question.
I checked Simon Woods excellent presentations
(http://www.maths.bath.ac.uk/~sw283/) however if the answer is there I am
too stupid to see it. In truth the content assumes a level of basic
understanding that I don't have. Unfortunately I do not have access to the
book ( Wood S.N. (2006) Generalized Additive Models: An Introduction with R.
Chapman and Hall/CRC Press.) or finances necessary to get it.
Any help would be much appreciated,

R version 2.10.1 (2009-12-14)
i386-pc-mingw32

locale:
[1] LC_COLLATE=English_United Kingdom.1252  LC_CTYPE=English_United
Kingdom.1252  
[3] LC_MONETARY=English_United Kingdom.1252 LC_NUMERIC=C                          
[5] LC_TIME=English_United Kingdom.1252   

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base    

other attached packages:
[1] mgcv_1.6-1

loaded via a namespace (and not attached):
[1] grid_2.10.1        lattice_0.17-26    Matrix_0.999375-33 nlme_3.1-96      
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