docs(website): align mempalaceofficial.com with honest benchmarks

Part of #875. Bring the VitePress site into line with the new README
and the reproducibility scorecard: drop category-error comparisons,
drop retracted claims, retain only metrics and caveats that survive
audit.

website/index.md
 - New tagline matches README (local-first, verbatim, pluggable backend,
   96.6% R@5 raw, zero API calls).
 - Replace the "MemPalace hybrid 100% / Supermemory ~99% / Mastra
   94.87% / Mem0 ~85%" comparison table with a single honest table
   showing MemPalace's own retrieval-recall numbers (raw 96.6%,
   hybrid v4 held-out 98.4%). Add an explicit sentence explaining why
   we no longer publish a cross-system table on the landing page
   (retrieval recall vs QA accuracy are different metrics).
 - Soften the "ChromaDB-powered vector search" feature blurb to be
   backend-agnostic, since the retrieval layer is pluggable.

website/reference/benchmarks.md
 - Full rewrite of the retrieval-recall tables. No more "100%"
   headline; honest held-out 98.4% R@5 replaces it. Added the
   model-agnostic rerank result (99.2% R@5 / 100% R@10 with
   minimax-m2.7 via Ollama) to show the pipeline is not Haiku-specific.
 - Drop the LoCoMo "Hybrid v5 + Sonnet rerank (top-50) 100%" row.
   With per-conversation session counts of 19-32 and top_k=50, the
   retrieval stage returns every session by construction — the number
   measures an LLM's reading comprehension, not retrieval.
 - Drop the cross-system comparison tables. Link out to each project's
   own research page (Mastra, Mem0, Supermemory) for their published
   numbers and metric definitions.
 - Rewrite reproduction commands to use the correct repository and
   demonstrate the new --llm-backend ollama flag.

website/concepts/the-palace.md
 - Remove the "+34%" row / paragraph. Wing/room filtering is standard
   metadata filtering in the vector store, not a novel retrieval
   mechanism — the April-7 note already retracted that framing; this
   finishes the retraction on the website where it had remained.

website/guide/searching.md
 - Same treatment for "34% retrieval improvement". Reframe as
   operational scoping, not a novel boost.

website/reference/contributing.md
 - Update the "palace structure matters" bullet to reflect the same
   framing: scoping-not-magic.

website/concepts/knowledge-graph.md
 - Replace the MemPalace-vs-Zep feature matrix with a short "related
   work" note that links to Zep's own documentation for authoritative
   details on their deployment model. Avoids claims we cannot verify
   at source.

website/guide/searching.md

@@ -23,23 +23,16 @@ mempalace search "deploy process" --results 10
 
 ## How Search Works
 
-1. Your query is embedded using ChromaDB's default model (`all-MiniLM-L6-v2`)
-2. The embedding is compared against all drawers using cosine similarity
-3. Optional wing/room filters narrow the search scope
-4. Results are returned with similarity scores and source metadata
+1. Your query is embedded using the vector store's default model (`all-MiniLM-L6-v2` with the default ChromaDB backend).
+2. The embedding is compared against all drawers using cosine similarity.
+3. Optional wing/room filters narrow the search scope — standard metadata filtering in the underlying vector store.
+4. Results are returned with similarity scores and source metadata.
 
-### Why Structure Matters
+### Why Scoping Matters
 
-Tested on 22,000+ real conversation memories:
+Wing/room filtering is useful when a single palace contains many unrelated projects or people. Narrowing the search to a specific wing (or wing + room) means the vector store only scores candidates inside that scope, which keeps retrieval predictable as the palace grows.
 
-```
-Search all closets:          60.9%  R@10
-Search within wing:          73.1%  (+12%)
-Search wing + hall:          84.8%  (+24%)
-Search wing + room:          94.8%  (+34%)
-```
-
-Wings and rooms aren't cosmetic — they're a **34% retrieval improvement**.
+This is a metadata-filter feature of the vector store, not a novel retrieval mechanism. Treat it as an operational convenience: clear scoping rules that a human or an agent can apply predictably.
 
 ## Programmatic Search