docs: resolve OQ-04, remove OQ-07, enrich OQ-03 with rolling windows

- OQ-04 resolved: thresholds are both model-specific (shipped with
  codebook) and user-overridable. Inspired by platonic representation
  hypothesis — calibrated models converge on similar behavioral patterns.
- OQ-07 removed: Rust port is an alknet project concern, not relevant
  to the Python package architecture. Removed from overview.md Phase 3.
- OQ-03 enriched: rolling window token screening for granular detection
  in documents (PDF→markdown use case, academic paper injection detection).
  Upgraded from low to medium priority.
- OQ-01 updated: likely path is PyTorch first, ONNX export by default.
- OQ-05 updated: needs deep dive into guardrail landscape.
- Updated threshold description in configuration.md with platonic
  representation context.

docs/architecture/overview.md

@@ -64,9 +64,9 @@ for the full threat analysis and academic evidence.
 
 - **Phase 3**: Advanced capabilities
   - Multi-turn attack detection (payload splitting)
-  - Streaming input screening
+  - Streaming/rolling-window input screening (granular detection for documents)
   - Custom model fine-tuning for domain-specific detection
-  - Rust port via burn/cubecl (speculative, requires R&D)
+  - ONNX Runtime inference backend (export from PyTorch)
 
 ### Out of Scope