This question & answer discussion has a peculiar character to it. Both @PeterEllis and @Michelle have provided decent answers (your question was also addressed by @onestop in the comments). Your question and your responses to these answers indicate that you need to think through what you are asking more thoroughly.
For example, when you say that "a low-score high-value rating (e.g. a rating of 5 with an informativeness score 0.05/1) might be equivalent or even higher than a high-score low-value rating (e.g. a rating of 1 with an informativeness score 0.25 or a rating of 1 with an informativeness score 0.2/1)", you evidence a lack of understanding. (I mean no disrespect here.) If those 'informativeness scores' are accurate, this is exactly what is supposed to happen and it will optimally incorporate the information in the ratings and the information in the scores according to that scheme. You can question the accuracy of the 'informativeness scores' or prefer a different scheme, but once you've ascented to these, that is the answer.
@Michelle offers a potential alternative scheme, that may be more appropriate depending on what you want to optimize. It is odd to criticize this by saying that "the rating picked by the high-skill expert is not taken into account in any way in the final result", because that is the point of this scheme.
This all reminds me of a famous (cranky) paper by Guttman, What is Not What in Statistics:
48. Permission is not required in data analysis
What is required is a loss function to be minimized. Practitioners
like to ask about a priori rules as to what is "permitted" to be done
with their unordered, ordered, or numerical observations, without
reference to any overall loss function for their problem. Instead,
they should say to the mathematician: "Here is my loss function: how
do I go about minimizing it ?"
It sounds to me like you need to figure out what you think is the optimal way to incorporate multiple sources of information with these characteristics. 'Optimal' depends on your goals, and the other stuff falls out from that. The Sage monograph Summated Rating Scale Construction: An Introduction may help you to think through these issues.
On the other hand, if your real concern is the validity of the 'informativeness score', this website might help you think through the pros and cons of different approaches to inter-rater agreement.
I apologize if it seems like this has a hectoring tone; I don't mean to come across that way. But your questions cannot be answered until you clarify these issues for yourself.