fix: Relax SearchResult validation to support DBSF fusion scores > 1.0

Fix false-positive validation error where DBSF (Distribution-Based Score
Fusion) correctly produces scores > 1.0 but SearchResult validation
incorrectly rejected them.

**Root Cause**: SearchResult.__post_init__() enforced scores in [0.0, 1.0]
range, but DBSF sums normalized scores from multiple retrieval systems
(dense semantic + sparse BM25), resulting in scores like 1.55 when both
systems strongly agree a document is relevant.

**Changes**:
- Relaxed validation to allow any score ≥ 0.0 (algorithms.py:147-157)
- Updated SearchResult and SemanticSearchResult documentation to explain
  score ranges for RRF ([0.0, 1.0]) vs DBSF (unbounded)
- Added comprehensive test coverage for both fusion methods
- Added DBSF fusion option to vector visualization UI
- Updated viz routes and vizApp() to support fusion parameter selection

**Testing**: All 157 unit tests pass, type checking passes, ruff passes

Fixes error: "Configuration error: Score must be between 0.0 and 1.0, got 1.1528953"

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

nextcloud_mcp_server/models/semantic.py

@@ -19,9 +19,22 @@ class SemanticSearchResult(BaseModel):
         default="", description="Document category (notes) or location (calendar)"
     )
     excerpt: str = Field(description="Excerpt from matching chunk")
-    score: float = Field(description="Semantic similarity score (0-1)")
+    score: float = Field(
+        description=(
+            "Relevance score (≥ 0.0, higher is better). "
+            "Score range depends on fusion method: "
+            "RRF produces scores in [0.0, 1.0], "
+            "DBSF can exceed 1.0 (sum of normalized scores from multiple systems)"
+        )
+    )
     chunk_index: int = Field(description="Index of matching chunk in document")
     total_chunks: int = Field(description="Total number of chunks in document")
+    chunk_start_offset: Optional[int] = Field(
+        default=None, description="Character position where chunk starts in document"
+    )
+    chunk_end_offset: Optional[int] = Field(
+        default=None, description="Character position where chunk ends in document"
+    )
 
 
 class SemanticSearchResponse(BaseResponse):