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11 changes: 10 additions & 1 deletion .claude/plans/splat-native-ultrasound-v1.md
Original file line number Diff line number Diff line change
Expand Up @@ -152,7 +152,16 @@ The palette codec is currently `(centroid_palette: u8, edge_weight: u8, scent: u

**Compose-table size doubles** (from 256×256×1 B to 256×256×2 B) — still fits in 128 KB, still L1-resident.

**Tests:** palette compose against ground-truth Gaussians; SH-basis discrimination (cosine ≥ 0.95 against analytic SH on phantom data).
**ADR-024 adoption (palette256 + HHTL codec, OGAR #39).** D-SPLAT-4 is named in `OGAR/docs/ARCHITECTURAL-DECISIONS-2026-06-04.md § ADR-024 Consequences` as one of the two queued ADR-024 adopters (paired with D-OSM-2 — see `cesium-osm-substrate-v1.md §11` for the geographic-side adoption note). Mapping ADR-024's four-step adoption checklist onto D-SPLAT-4:

1. **Prefix.** FMA NiblePath + SH basis-id — the per-region spatial frame (FMA class identity within the atlas + SH basis index spanning the ℓ≤3 carrier).
2. **Palette domain.** Quantized SH coefficients (16 coefficients spanning ℓ≤3 — degree 0: 1, degree 1: 3, degree 2: 5, degree 3: 7 — totaling 16, matching the §3 D-SPLAT-1 carrier shape) clustered per FMA region. Per-region palette captures dominant tissue echo signatures (planar fascia / spherical organ surfaces / Doppler-flow vascular).
3. **ρ-vs-reference target ≥ 0.99**, matching the `lance-graph-arm-discovery` aerial-codebook empirical anchor (ρ = 0.9973 vs cosine). Reference: analytic SH evaluation at the same view direction (the same reference used in the D-SPLAT-4 test plan below). Report empirical ρ on the **first FMA-region palette build** (default region: femur cortical bone — smallest tractable corpus; cf. OGAR PR #30 §6 FMA-bones litmus).
4. **Decode = const-table lookup.** Per-region SH palette is runtime const-table; decode path is zero-allocation. Compile-time HHTL where the palette is shared across regions (e.g. global basis-ID lookup for the 256 SH signatures).

The 256-ceiling escape hatches from ADR-024 apply directly: per-region palettes are the cheapest answer (different FMA region, different 256 SH-signature entries); hierarchical palettes (coarser at OrganSystem level, finer per Bone leaf) mirror the SH ℓ=0/ℓ=1 vs ℓ=2/ℓ=3 split. Palette-64K is reserved for measured-cardinality escalation, not speculation.

**Tests:** palette compose against ground-truth Gaussians; SH-basis discrimination (cosine ≥ 0.95 against analytic SH on phantom data); **NEW: empirical ρ-vs-reference reported on first FMA-region palette build (target ≥ 0.99 per ADR-024 adoption contract)**; per-region palette cardinality distribution (mean / p95 / p99) at FMA region granularity.

**Gates on:** D-SPLAT-1.

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