# Subgroup Breakdown Report

## Scope

- Source analysis run: `20260526_v2_official20_plus_c2patch_plus_subgroupconditionalrepair_merged49`
- Family analyzed: `subgroup_structure`
- Excluded models: `cdtd, codi, goggle`
- Included models: `12`
- Deduplicated dataset-model panels: `559`
- Subgroup query rows used: `12515`

## Canonical decomposition

- `subgroup_structure = 0.5 * internal_profile_stability + 0.5 * subgroup_size_stability`
- `internal_profile_stability` captures subgroup-internal feature/distribution behavior.
- `subgroup_size_stability` captures whether subgroup support/size structure is preserved.

## Main findings

1. `REAL` is the expected perfect upper bound with subgroup score `1.000`. Among synthetic generators, `RealTabFormer` is strongest with mean subgroup score `0.790` across `49` datasets.
2. `BayesNet` leans most toward internal-profile preservation (profile minus size = `0.002`), while `ForestDiffusion` is the clearest size-heavy model (profile minus size = `-0.033`).
3. `TabDDPM` is the most balanced model between the two subgroup branches with mean absolute branch gap `0.000`.
4. Dataset difficulty is uneven: `n9` is the hardest dataset on subgroup score (`0.091` mean across models), while `c3` is the easiest (`1.000`).

## Files to use first

- `figures/subgroup_tradeoff_scatter_main.pdf`
- `figures/subgroup_branch_dumbbell_main.pdf`
- `figures/subgroup_prefix_bars_appendix.pdf`
- `tables/subgroup_model_summary_generated.tex`
- `data/model_summary.csv`

## Prefix note

- Prefix coverage summary rows: `36`
- The `c / m / n` split is exported explicitly because subgroup behavior differs by dataset family, not just by overall model average.