Chap 8 in Book Differs from Notebook

[YMandCL]

In Chapter 8 of the book you use Logistic Regression for the "Meta-Learner".
Accuracy from GaussianNB: 0.3913333333333333
Accuracy from KNN: 0.697
Accuracy from Decision Tree: 0.728
Accuracy from Meta Learner: 0.7746666666666666

However, in the Notebook you use GaussianNB as the "Meta-Learner". The notebook appears a bit incomplete, but if you follow the book you get the following results:
Accuracy from Logistic Regression: 0.7746666666666666
Accuracy from KNN: 0.697
Accuracy from Decision Tree: 0.7333333333333333
Accuracy from Meta Learner: 0.772

I'm not really sure what is going on here. It appears the "Meta Learner" from the book is simply outputting Logistic Regression results.

Yet, using GaussianNB as the "Meta Learner" improves upon the GaussianNB accuracy but is no better than Logistic Regression.

I could be off on my code, but any clarification you could provide would be much appreciated.