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Perhaps the scaling factor is not from individual, but total variance is fixed.
Assume that the MSE ratio equals the reciprocal of (original effective degrees of freedom + new), but to save time, and given the context, perhaps the total observations increased because more features were added.
The only logical conclusion: 4 new features were added, so total observations is original plus 4, but what was original?
Initial MSE 49, final 36, both in the same model with more features, so likely the number of initial observations is not limited to n, but the added samples are not known.
But the question asks for total observations after fine-tuning.
Suppose initially there were 25 samples (given in context: original dataset had 25 observations).
Initial: n + k = 25, but k=1 (model), so n=24 features? Unrealistic.
Perhaps n is number of independent variables.
Therefore, the number of test samples is still 100
So number of samples remains 100, but number of features may change, or model capacity increases, but number of observations is unchanged.
