feat(weights): integrate sample_weight composition into both train() data split paths

feat(weights): integrate sample_weight composition into both train() data split paths

Add _train_default() mirroring BaseRegressionModel.train() with _compose_train_weights inserted between make_train_test_datasets and _apply_pipelines. Routes train_test_split path through _train_default instead of super().train(). Inserts _compose_train_weights before _apply_pipelines in timeseries_split path. Calls _strip_label_weight_columns(dk) at top of train() for both branches. Validated locally with pytest + structural AST checks (evidence: .omo/evidence/task-9-{pytest,structural}.txt).