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It is not easy for to understand how the environment can me summarized by a sigle number t (for temperture). Can we take an example in order for me to understand your point.
The main point is that the theory is heuristic. As I am sure you know, the best play is not always the biggest play.
The other point is that games add and subtract. This is the basis for combinatorial game theory (CGT). Go players did not come up with that idea, but they do realize that the interaction between independent positions matters, even without ko. The thing is, then, that if you have information about other games that is relevant, it is not part of the environment. It is foreground knowledge, not background.

(BTW, I came up with the idea of the environment independently, long before I heard about CGT, just from studying go endgames.

)
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Let's take as the local region the upper left corner in the diagram above.
First of all I try to count the position:
If it is white to play, white plays "a" and the score (for black point of view) is -23.
If is is black to play, black plays "a" and we reach a position where white or black can then play "b".
if now black plays "b" the score is +0
and if now white plays "b" the score is -6
As a consequence after black "a" the position is estimated -3 (the average value between +0 and -6)
Finally the initial position is evaluate -13 (the average value between -23 and -3).
On average the "a" move earns 10 points and then the "b" move earns 3 points.
Right.

Furthermore, if the ambient temperature is less than 3 and Black plays first, White replies locally. Even though this is a gote position, Black can play with sente under those conditions.
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Now let me take two scenarios for the environment:
S1 : four gote areas which earn : 11, 8, 5 and 2 points
S2 : five gote area which earns : 10, 8, 6, 4, 2 points
The term, environment, has more than one sense. For evaluation purposes we only care about its temperature. But if we want to include more information, then we add together all the other areas of interest to the original game to get a new game.
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In the S1 scenario black has to play in the environment but in the S2 scenario black has to play locally.
I do not know what is the temperature of S1 or S2 but my feeling is that, depending of the temperature definition, I will probably be able to build two different environments with the same temperature and different play for black.
The temperature of S1 is 11, the temperature of S2 is 10. Your second statement is true, because the theory is heuristic. It's not always right to play the averages.
For instance, suppose that your original position plus a simple gote with an average value of 0 in which a play gains 11 pts. are the only unplayed positions left on the board with Black to play. Even though Black's play gains only 10 pts. in your original position Black should play there. Then after White replies in the other position, Black can take the last play for an additional 3 pts. Black's total gain is then 10 - 11 + 3 = 2 pts. instead of 11 - 10 = 1 pt.
Note that this calculation is at temperature 0. If we include an environment for the combined game, Black's total gain at temperature t when she takes the 10 pt. play first is 2 - t pts. That is better, on average, than taking the 11 pt. play first when 2 - t > 1, i.e., when 1 > t. So above temperature 1 Black's average gain is better by taking the 11 pt. gote.
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May be I could agree temperature may be a great "help" to guess the correct move but in any case you have to read a great part of the yose, haven't you?
The theory gives you a good guess to the best play in most circumstances. That's why go players came up with it in the first place.

Tristan Cazenave has even done some research on the effectiveness of always playing the biggest play in actual games. It works well. Big duh.
But also, when you are reading extensively, the theory gives you a good first sequence of plays to read.
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In my example the "standard" method to guess the correct move is "simply" to estimate the local situation (here 10 points) and to verify this guess by reading the yose. For the time beeing I do nont really see the advantage of the temperature notion. I suspect my example is not that significant for the temperature notion.
In a real game the ambient temperature is usually close to that of the gain from taking the biggest play. However, there are occasions when it is rather less. In such cases, as my example of the combined game illustrates, you may be able to figure out when the biggest play is probably not best.
