Linear functional boosting scores

I'm trying to understand the scoring for linear functional boosts in Elastic App Search.

It says the factor field can range from 0 to 10, defaulting to 1. It also says "A negative factor or fractional factor will not deboost a result.".

Firstly, if the factor can only range from 0 to 10, I don't know why the documentation is talking about a negative factor.

Secondly, and more importantly, I would like to know what the calculation behind the scenes is. For example, if I have Document A with a field, say Visitors = 10, and a Document B, with Visitors = 100, and I apply a linear functional boost of 0.2, then what is the Boost Value of each document, which is to be combined with the Original Document Score? And how is this Boost Value arrived at, for each of the documents?

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