Add DR and plug-in T scoring metrics for CATE model evaluation

[aman-coder03]

Proposed changes

this pr adds two new observed-data surrogate metrics for evaluating fitted cate models without access to true counterfactual outcomes

what's included

• added compute_dr_pseudo_outcomes() to construct cross-fitted doubly robust (aipw) pseudo-outcomes that can be reused across different evaluation methods
• added dr_score() to evaluate cate models using mean squared error against the dr pseudo-outcomes
• added plug_in_t_score() to evaluate cate models against a cross-fitted plug-in t-learner cate proxy
• reused the same pseudo-outcomes with rate_score() to avoid fitting nuisance models multiple times
• added optional half-sample bootstrap confidence intervals and p-values, following the existing rate_score() implementation
• added unit tests covering pseudo-outcome generation, model ranking, bootstrap inference, error handling, and compatibility with rate_score()
• added documentation explaining the methodology and intended use of the new metrics

closes #922

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