feat(ruview-unified): unified RF spatial world model P1 (ADR-273..278)

One shared representation instead of another isolated RF classifier: new
v2 leaf crate ruview-unified implementing all five ADR-273 pillars, plus
six ADRs with measured, grade-labeled results.

- Canonical RfTensor + fail-closed hardware adapter registry (802.11 CSI
  via wifi-densepose-core::CsiFrame, FMCW radar cubes, UWB CIR, 5G SRS);
  shared layout/gain/phase normalization proven by tests (ADR-274).
- Universal RF foundation encoder: CFO-aligned, median-scaled tokenizer;
  masked-reconstruction pretraining with hand-derived backprop verified
  against central finite differences (max rel err 1.31e-5 over all 12
  parameter groups); fusion contract z = Enc ⊙ σ(AgeEnc) + GeomEnc;
  task adapters under the 1% budget (129/268/387/2 params vs 40,856
  backbone), enforced by test.
- RF-aware Gaussian spatial memory: anisotropic primitives with per-band
  reflectivity, confidence-weighted fusion, decay, spatial-hash/semantic
  queries, closed-form Beer-Lambert channel gain (exact Friis on empty
  map), inverse gain updates (unseen 6.1 dB wall learned to <0.5 dB in
  20 observations), task-gated scene graph (ADR-275).
- Physics-guided synthetic RF worlds: image-method multipath (order ≤2),
  complex-permittivity Fresnel materials, emergent Doppler proven against
  the analytic phase rate, seeded ChaCha20 randomization of physics and
  hardware nuisances; byte-deterministic per seed (ADR-276).
- Edge sensing control plane: 802.11bf/ETSI-ISAC-aligned purposes/zones,
  fail-closed authorization, double-gated identity, retention bounds;
  BoundedEvent-only trust boundary makes raw RF export unrepresentable
  (ADR-277). Radar inverse rendering stays a gated research program
  (ADR-278, no code by design).

Anti-leakage acceptance pipeline (strict splits by room/day/person/
chipset/firmware/layout with independent disjointness verification):
presence F1 1.00 on held-out rooms and held-out chipset, degradation
0.0, ECE 0.012, p95 latency 2.0 ms debug / 105 µs release — ALL
SYNTHETIC until P2 real-data validation.

Benchmarks + optimization pass: channel_gain 139→27 µs (O(1) in map
size via segment-corridor AABB sweep), observe_link 305→74 µs, DFT
twiddle plan 4.9x; hash/linear crossover (~4k Gaussians) reported
honestly.

Tests: ruview-unified 66 unit + 3 acceptance, 0 failed; workspace
3,771 passed 0 failed (--exclude wifi-densepose-desktop: GTK headers
unavailable in this container). Python proof: VERDICT PASS. Also
gitignore sensing-server test-run artifacts (incl. generated
session-secret).

Co-Authored-By: claude-flow <ruv@ruv.net>
Claude-Session: https://claude.ai/code/session_01Q1R5zhz6sSfXGRXpgBwpFX

README.md

@@ -638,11 +638,12 @@ Verify the plugin structure: `bash plugins/ruview/scripts/smoke.sh`. Full detail
 | [Semantic Primitives — Precision/Recall](docs/integrations/semantic-primitives-metrics.md) | Per-primitive F1 on the held-out paired-capture set: someone-sleeping, possible-distress, room-active, elderly-inactivity-anomaly, meeting, bathroom, fall-risk, bed-exit, no-movement, multi-room. |
 | [Claude Code / Codex Plugin](plugins/ruview/README.md) | The `ruview` plugin + marketplace — skills, `/ruview-*` commands, agents, and the Codex prompt mirror |
 | [Portable harness — `npx @ruvnet/ruview`](harness/ruview/README.md) | MetaHarness-minted, host-portable RuView operator harness — `ruview.*` MCP tools + the MEASURED-vs-CLAIMED honesty guardrail enforced in code ([ADR-182](docs/adr/ADR-182-npx-ruview-harness-via-metaharness.md)). A lighter, multi-host companion to the in-repo plugin. |
-| [Architecture Decisions](docs/adr/README.md) | 182 ADRs — why each technical choice was made, organized by domain (hardware, signal processing, ML, platform, infrastructure) |
+| [Architecture Decisions](docs/adr/README.md) | 201 ADRs — why each technical choice was made, organized by domain (hardware, signal processing, ML, platform, infrastructure) |
 | [Domain Models](docs/ddd/README.md) | 8 DDD models (RuvSense, Signal Processing, Training Pipeline, Hardware Platform, Sensing Server, WiFi-Mat, CHCI, rvCSI) — bounded contexts, aggregates, domain events, and ubiquitous language |
 | [rvCSI — edge RF sensing runtime](https://github.com/ruvnet/rvcsi) | Rust-first / TypeScript-accessible / hardware-abstracted CSI runtime: multi-source ingestion (incl. real nexmon_csi `.pcap` from a **Raspberry Pi 5** / Pi 4 / Pi 3B+ — CYW43455 / BCM43455c0) → validation → DSP → typed events → RuVector RF memory ([ADR-095](docs/adr/ADR-095-rvcsi-edge-rf-sensing-platform.md), [ADR-096](docs/adr/ADR-096-rvcsi-ffi-crate-layout.md), [domain model](docs/ddd/rvcsi-domain-model.md)). Now its own repo — [`ruvnet/rvcsi`](https://github.com/ruvnet/rvcsi) — vendored here under `vendor/rvcsi`; 9 `rvcsi-*` crates on crates.io, `@ruv/rvcsi` on npm, plus a Claude Code plugin. |
 | [Desktop App](v2/crates/wifi-densepose-desktop/README.md) | **WIP** — Tauri v2 desktop app for node management, OTA updates, WASM deployment, and mesh visualization |
 | `ruview-swarm` | Drone swarm control system (ADR-148) — hierarchical-mesh topology, Raft consensus, MARL, CSI sensing payload, MAVLink/PX4/ArduPilot compatibility, Ruflo AI-agent integration |
+| `ruview-unified` | Unified RF spatial world model ([ADR-273](docs/adr/ADR-273-unified-rf-spatial-world-model.md)..[277](docs/adr/ADR-277-edge-sensing-control-plane.md)) — canonical RF tensor + hardware adapters (WiFi CSI / FMCW radar / UWB / 5G SRS), universal RF foundation encoder with ≤1% task adapters, RF-aware Gaussian spatial memory with channel-gain queries + inverse updates, physics-guided synthetic RF worlds, and an 802.11bf/ETSI-ISAC-aligned sensing policy plane (raw RF structurally unexportable). All accuracy numbers SYNTHETIC until real-data validation. |
 | [Medical Examples](examples/medical/README.md) | Contactless blood pressure, heart rate, breathing rate via 60 GHz mmWave radar — $15 hardware, no wearable |
 | [Extended Documentation](docs/readme-details.md) | Latest additions, key features, installation, quick start, signal processing, training, CLI, testing, deployment, and changelog |