docs: 2026-05-29 audit corrections (docs)

02-architecture/BIOMETRIC_ENGINE_ARCHITECTURE.md

@@ -279,7 +279,7 @@ Nice to have. Server-side alternatives exist for all of these.
 |-----------|---------------|-----------------|
 | `PassiveLivenessDetector` | Texture/color/moire liveness scoring | Server-side liveness via `biometric-processor` is the primary authority. Client-side is supplementary. Gabor convolution is expensive; defer to Phase 3. |
 | `EmbeddingComputer` | ONNX face embeddings | Server-side DeepFace embedding via REST API. **Note:** MobileFaceNet was removed per ADR 0003 (2026-04-18); the active client path is geometry-512 (landmark-based fallback). |
-| `CardDetector` | ONNX YOLO card detection | Server-side YOLO (current production path) |
+| `CardDetector` | ONNX YOLO card detection | None — client-only in production; the server-side YOLO card path was removed (web-app #111) |
 
 ---
 

09-auth-flows/01-PLATFORM_CAPABILITY_MATRIX.md

@@ -147,10 +147,10 @@ FIVUCSAS supports **5 client platforms** and **10 authentication methods** acros
 #### Card Detection (ID Document Scan)
 - **Input**: Camera captures image of physical document
 - **Platforms**: All camera-equipped devices
-- **Dependencies**: Biometric Processor API (`/api/v1/card/detect` - YOLO-based)
-- **Processing**: Server-side (image classification + OCR)
+- **Dependencies**: In-browser ONNX YOLOv8n (client-side detection, web-app #111); Biometric Processor API only for OCR/MRZ on the captured crop
+- **Processing**: Client-side detection/classification; server-side OCR only
 - **Enrollment**: Capture front/back of ID document, extract and verify data
-- **Offline Capable**: No (requires biometric processor)
+- **Offline Capable**: Detection yes (client-side ONNX runs without server); OCR/MRZ extraction still requires the biometric processor
 
 ---
 

09-auth-flows/03-ENROLLMENT_FLOWS.md

@@ -653,7 +653,7 @@ Step 1: Document Photo Capture
   - Capture front of ID document
 
 Step 2: Document Classification
-  - POST /api/v1/card/detect (biometric processor, YOLO-based)
+  - In-browser YOLOv8n ONNX detection (client-only, web-app #111; no server round-trip)
   - Detect document type: passport, national ID, driver's license, etc.
 
 Step 3: Data Extraction

plans/CLIENT_SIDE_ML_PLAN.md

@@ -43,7 +43,7 @@ The server has no GPU. All heavy ML **inference for auth decisions** stays serve
 | Voice VAD | **Primary** (Phase 4, this plan) | — | In progress |
 | Voice embedding | — | **Only** (Resemblyzer 256-dim) | Server only, V2 may revisit |
 | Voice 1:1 verify | — | **Only** | Server only |
-| Card detection | **Primary** (YOLOv8n ONNX / WASM) | Fallback | Wired, awaiting model file (Phase 3) |
+| Card detection | **Only** (YOLOv8n ONNX / WASM, in-browser) | — | Live — client-only; server fallback removed (web-app #111). True 12.3 MB YOLOv8n delivered + integrated (web-app #109, biometric-processor #116) |
 | Card OCR + MRZ | — | **Only** | Server only |
 | Proctoring gaze / deepfake / object | — | **Only** | Server only |
 
@@ -80,10 +80,10 @@ Live in browser. No action needed. Model bundled with MediaPipe runtime.
 | Property | Value |
 |---|---|
 | Format | ONNX (WASM) |
-| Size | ~6.2 MB |
+| Size | ~12.3 MB (true YOLOv8n, opset 12) |
 | Input | 640×640 RGB (letterboxed) |
 | Output | Bounding boxes + class |
-| Role | Real-time client overlay; crop sent to server for OCR + MRZ. Server fallback on missing model. |
+| Role | Real-time client overlay + detection (client-only); crop sent to server for OCR + MRZ. No server fallback for detection (removed, web-app #111). |
 
 ### 4.5 Passive Liveness — MobileNet-v3 Anti-Spoof
 Currently heuristic (texture/moire/color) in `PassiveLivenessDetector.ts`. No neural model. Phase 5 will wire it into a gating threshold or demote it — no new model purchase required.
@@ -105,7 +105,7 @@ Currently heuristic (texture/moire/color) in `PassiveLivenessDetector.ts`. No ne
   "base_url": "https://app.fivucsas.com/models",
   "files": [
     {"name": "mobilefacenet.onnx", "sha256": "<hash>", "bytes": 4915200},
-    {"name": "yolo-card-nano.onnx", "sha256": "<hash>", "bytes": 6500000},
+    {"name": "yolo-card-nano.onnx", "sha256": "<hash>", "bytes": 12300000},
     {"name": "silero-vad.onnx",    "sha256": "<hash>", "bytes": 1850000}
   ]
 }

presentations/SPRING_2026_FINAL_PRESENTATION.md

@@ -567,7 +567,7 @@ function App() {
 | High | Widget dogfooding — use own widget in web-app login | In Progress |
 | High | Mobile app backend integration tests | URLs configured |
 | Medium | SMS gateway (Twilio) production activation | Code ready |
-| Medium | Client-side ONNX card detection (replacing server YOLO) | In Progress |
+| Medium | Client-side ONNX card detection (replacing server YOLO) | Done (web-app #111; server YOLO card path removed) |
 | Low | ISO/IEC 30107 compliance certification | Future |
 | Low | Full WebAuthn attestation (CBOR) | Research |
 | Future | iOS app UI implementation | Framework ready |