feat(selene): retire the seat; chat-judge -> gen, selene-1-mini-8b 404s by design

Benchmarked selene against gen on selene's own job: 24 designed judge items
with checkable ground truth, pairwise + absolute modes, 3 repeats, on BOTH a
neutral JSON prompt and Selene's native Atla template. 288 calls, all free
local.

  neutral JSON     selene 20/24 (83%)   gen 23/24 (96%)
  native Atla      selene 21/24 (88%)   gen 22/24 (92%)

gen won on both templates and selene's BEST sat below gen's WORST. Selene was
given its own fine-tuned template as a fairness check; it gained one point,
not the three it needed.

Decisive defect: selene cannot emit "tie" -- 0/2 on both templates, forcing a
winner on every equivalent pair. For eval work that is the case that matters
most. gen returned tie correctly on the JSON template. Selene also compressed
the 1-5 scale (clustered at 2s and 4s) where gen used it fully. Selene's only
win was ~3x latency, unexercised at ~60 calls/day with zero queueing.

TWO NAMES, TWO DIFFERENT TREATMENTS, deliberately:

- chat-judge -> repointed to gen. It is a ROLE alias and ADR-0012 says
  consumers bind the capability, not a concrete model. Sampler profile copied
  from image-judge (temp 0, top_p 1.0, top_k 1, thinking off) so the served
  config matches the benchmarked condition.

- selene-1-mini-8b -> REMOVED. It 404s. It was NOT aliased to gen. A
  served-name is a contract about what the model IS; answering it with a
  different model hides a material change behind a stable string. Operator
  ruling: "never repoint a named model at a different model's endpoint --
  that is intentionally misleading." Verified: the gateway now returns
  HTTP 400 "Invalid model name" for it.

Reclaimed 17.2 GiB on ana-ml2 GPU 1 (free 1,818 -> 19,450 MiB) on a card that
had under 2 GiB of headroom. gen already runs on GPU 0, so the judge role
moved onto an existing seat rather than allocating anything new.

Canonical litellm config synced from the host; ana-ml2 README and
recommended-model-settings updated. compose.yaml kept for reference, not
deployed.

stacks/selene/README.md

@@ -0,0 +1,89 @@
+# selene — RETIRED 2026-08-23
+
+AtlaAI Selene 1 Mini (Llama 3.1 8B, dynamic FP8), served on ana-ml2 GPU 1 at
+`:8011` as `selene-1-mini-8b`. An LLM-as-judge: it scored and critiqued other
+models' output rather than generating for users (hallucination /
+RAG-faithfulness checks, Worldtree's Domari and selene-judgment roles).
+
+**The seat is down and the compose file is kept for reference only.** It is not
+deployed. `stacks-mirror/` will no longer show it on the host.
+
+## Why it was retired
+
+Benchmarked head-to-head against `gen` (qwen3.8-27b-uncensored, ana-ml2 GPU 0
+`:8015`) **on selene's own job** — 24 designed judge items with checkable
+ground truth, pairwise and absolute-scoring modes, 3 repeats each, run on two
+prompt templates. 288 calls total, all free local.
+
+| template | selene | gen |
+|---|---|---|
+| neutral JSON prompt | 20/24 (83%) | **23/24 (96%)** |
+| Selene's native Atla template | 21/24 (88%) | **22/24 (92%)** |
+
+**gen won on both templates, and selene's best score sat below gen's worst.**
+Selene was given its own fine-tuned prompt format as a fairness check — it
+gained one point, not the three it needed.
+
+**The decisive defect: selene cannot emit "tie."** On both tie items, on both
+templates, it forced a winner (0/2 each time). gen returned `tie` correctly on
+the JSON template. For eval work, close pairs are precisely the case that
+matters; a judge that manufactures a preference on every equivalent pair is
+producing noise exactly where it is most trusted.
+
+Other findings:
+
+- **Calibration.** gen used the full 1–5 range decisively (1s for bad answers,
+  5s for good). Selene clustered at 2s and 4s, compressing the scale.
+- **Stability at temperature 0.** Selene had 2 unstable items on the JSON
+  template; gen had 0. They swapped on the native template (gen 4, selene 0) —
+  longer free-text reasoning costs determinism.
+- **Latency was selene's only win** — roughly 3× faster (0.23s vs 0.40s median
+  on JSON). Unexercised: it served ~60 calls/day with zero queueing across five
+  weeks of uptime.
+- **Shared blind spot.** Both preferred a response containing an arithmetic
+  error on the JSON template. gen caught it on the reasoning-first template.
+  Neither is trustworthy for numerically-checkable judgments without a prompt
+  that forces reasoning before the verdict.
+
+Best measured configuration overall: **`gen` + the neutral JSON prompt** —
+23/24, zero instability, ties handled correctly.
+
+## What happened to the names
+
+**`chat-judge` → repointed to `gen`.** It is a *role* alias, and ADR-0012 is
+explicit that consumers bind the capability, not a concrete model. Sampler
+profile copied from `image-judge` (temperature 0, top_p 1.0, top_k 1,
+thinking off) so the served config matches the benchmarked condition.
+
+**`selene-1-mini-8b` → removed outright. It 404s by design.** It was NOT
+aliased to `gen`. A served-name is a contract about what the model *is*;
+answering it with a different model hides a material change behind a stable
+string, and the caller has no way to know. Failing loud forces a conscious
+migration. Operator ruling, 2026-08-23:
+
+> never repoint a named model at a different model's endpoint — that is
+> intentionally misleading
+
+Direct precedent on this gateway: `qwen-image-bench` / `image-judge` had their
+dedicated backend retired 2026-07-15 to reclaim GPU 1 VRAM and were repointed
+to `gen` as role aliases. Counter-example worth remembering: when
+`qwen3-reranker` was retired, `nevermore` was pinned to it *by name* and the
+cutover moved the `reranker` alias but never moved nevermore — which is why
+name-pinned consumers get notified explicitly rather than assumed covered.
+
+## Reclaimed
+
+```
+GPU 1 free:  1,818 MiB  →  19,450 MiB
+```
+
+17.2 GiB, on a card that had under 2 GiB of headroom. `gen` was already
+running on GPU 0, so the judge role moved onto an existing seat rather than
+allocating anything new.
+
+## To bring it back
+
+`compose.yaml` and the host `.env` are intact. GPU 1 must have ~17 GiB free
+(`SELENE_GPU_MEM_UTIL=0.17`); re-add the `selene-1-mini-8b` entry to the
+LiteLLM config **under its own true name**, never as an alias for something
+else.