Z-Score and Z-Probability in SQX: Clarify please

A. Can anybody clarify how to interpret Z-Score and Z-Probability for generated strategies in SQX?

B. Please clarify if the following are true:

1. If Z-Probability is high (eg 90%), there is a high chance that winners follow winners and losers follow losers.
2. If Z-Probability is low (eg 2.9%), the distribution of winning and losing trades in succession is random and unpredictable.
3. If Z-Score is large negative number (eg -1.9) but still within [-1.96, 1.96], then the strategy with good equity curve in backtests is more likely to remain profitable in the future
4. If Z-Score is large negative number (eg -2.9) but outside [-1.96, 1.96], then the strategy is more likely to fail in future because its behavior statistically changed recently
5. If Z-Score is large positive number (eg 1.75) but still within [-1.96, 1.96], then the strategy with good equity curve in backtests will be less profitable in the future because the Z-Score will revert to its a mean value around Z = 0
6. If Z-Score is a small number around zero (eg 0.8), then the strategy with good equity curve in backtests will not be robust in the future, because Z-Probability for a small Z-Score is also small

C. What is an ideal range of values for the following in the context of strategy development? (I already know the ranges in the general context of statistics that Probability can be anywhere from 0 to 100% and that Z-Score ideally lies in [-1.96, 1.96] for OOS sample that is truly representative of the population data of IS)

1. Z-Score
2. Z-Probability

D. Are Z-Score and Z-Probability more accurate for Strategies with higher degrees of freedom?

E. Are Strategies with no Exit rules (i.e they exit only via SL, TP, Trailing, Exit after N bars/EOD/TimeRange) likely to maintain a steady Z-Probability than those with rule based exit conditions?

F. Assuming that it is a good idea to add Cross Checks during Build process for a certain Z-Probability or Z-Score during Training period

1. Is it better to add a Cross Check for Z-Score only or Z-Probability only or both?
2. What is a meaningful threshold value, signed for Z-Score and unsigned for Z-Probability?
3. Is it a good idea to add a Cross Check to discard strategies with |z| > 1.96 ?