Featurizer 0.6.0

Set-based pre-aggregation for the correlated-subquery aggregator tier — the
performance follow-up ADR-0009 deferred. Removes the full-cohort scaling cliff
while preserving output column names (ADR-0007) and values exactly.

Added

• Set-based pre-aggregation path (ADR-0010). Each of the 27 migratable
  subquery aggregators now emits one companion CTE — a single window (or
  grouped-join) pre-pass over the child stream reduced by a plain GROUP BY —
  instead of a scalar correlated subquery evaluated once per target row. Cost
  drops from O(target_rows × subqueries × child_scan) to one O(N log N) pass
  per family. Opt-in per aggregator via SubqueryAggregator._build_preagg; the
  companion CTE reuses the existing join / synth-pruning / sharding /
  materialization machinery unchanged.
• Golden-value regression harness.
  tests/integration/test_preagg_value_equality.py +
  tests/fixtures/preagg_golden_values.json freeze the v0.5.2 correlated values
  (162 cases) and assert every migrated aggregator reproduces them exactly.
  tests/test_preagg_shape.py adds DB-free companion-CTE shape guards. A
  benchmarks/ package (outside the wheel) measures the scaling curve.

Changed

• Advanced-aggregator full-cohort materialization is now practical. Measured
  on a synthetic 10k-parent cohort, the all-aggregator matrix went from >300 s
  (timeout, censored) to 2.6 s; the worst individual families improved
  ~150–390× (mean_deviation 93.9 s → 0.24 s, trimmed_mean_10 94.6 s →
  0.27 s, theil 70.2 s → 0.45 s). The default-active tier is unchanged. Output
  column names and values are byte-/value-identical to v0.5.2 (proven by the
  golden harness + the ADR-0007 name-stability snapshot).
• Families migrated: gap (gap_mean/stddev/min/max, gap_cv, burstiness),
  categorical (entropy, hhi), numeric-stream (gini, mean_deviation,
  theil, acf_1, variance_ratio, cosinor_amplitude_weekly,
  trimmed_mean_10, median_absolute_deviation), and sequence/transition
  (ngram_2_freq, ngram_3_freq, sequence_entropy, longest_streak,
  state_volatility, transition_matrix_summary, rework_count,
  recurrence_interval, markov_conditional_entropy, max_transition_prob,
  time_in_current_state).

Not migrated (intentional)

• The special-config families keep the correlated path: predicate-driven
  (first_passage_time, cross_type_latency, right_censoring_indicator),
  two-window drift (kl_drift, wasserstein_drift), and spatial
  (distance_travelled, radius_of_gyration, spatial_std, bbox_area). They
  fire only under special config and are out of the full-cohort scope; they
  migrate later only if a real workload demands it.