llm_directed: directed sex (breed offspring + select on verifier) — E10 in real weights

Adds the "directed sex" operator (E10) the moe regime-flip pointed to: don't
commit to one a-priori blend — breed a population of recombinant offspring
(specialists merged at Dirichlet-sampled weights), score each on a held-out
validation split with the verifier, and keep the fittest, reported on a fresh
test split. Two breeding objectives: best-overall and best-worst-family.
src/llm/directed.py + kind llm_directed, reusing the cached specialists.

Result — refinements pay off in proportion to how far the uniform soup is from
optimal:
- 0.5B (soup dilutes): directed selection beats soup on the bred objective —
  directed_overall 0.69 > soup 0.64; directed_balanced worst-family 0.37 > 0.26.
  Riders: single-objective selection trades off the other axis (overall-breed
  tanks lists to 0.17); a global blend still trails per-input routing (0.74).
- 7B (Imperial CX3, soup already composes to ceiling on near-saturated families,
  strings/arith 1.00): directed ~= soup (0.868 ~ 0.873, marginally below via a
  val/test overfit gap) — no fitter offspring to breed.

Through-line across all four LLM runs: "merge, don't average" and its refinements
(routing, directed selection) are weak-base / suboptimal-default phenomena — they
help at 0.5B and are inert at 7B. Honest limitation kept in the writeup: the 7B
families are near-saturated, which caps the headroom; a harder unsaturated
benchmark is the fair next test.

Also folds in the two llm_moe local manifest/config files missed in 8da0dac.
+3 directed unit tests (130 green). Results in results/llm_directed{,_hpc}/
(parquet gitignored).

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

hpc/llm_directed.pbs

@@ -0,0 +1,22 @@
+#!/bin/bash
+# Directed sex (llm_directed) on an L40S (46 GB) — breed recombinant offspring + select on the verifier.
+# Reuses the cached 7B specialist adapters (models/llm/spec_*) if present. Same env as the other LLM
+# jobs (see hpc/README.md): uv sync --extra dev --extra neural --extra llm + pre-download the 7B base.
+#   submit:  qsub hpc/llm_directed.pbs      status: qstat -u $USER
+#PBS -l select=1:ncpus=8:mem=64gb:ngpus=1:gpu_type=L40S
+#PBS -l walltime=02:00:00
+#PBS -N lam_llm_directed
+
+cd "$PBS_O_WORKDIR"
+export HF_HOME="$EPHEMERAL/hf_cache"
+export TOKENIZERS_PARALLELISM=false
+export UV_CACHE_DIR="$EPHEMERAL/uvcache"
+
+source .venv/bin/activate
+nvidia-smi --query-gpu=name,memory.total,driver_version --format=csv,noheader
+
+python -m llm.experiment configs/llm/directed_hpc.yaml
+
+# results/llm_directed_hpc/ written in-place (parquet gitignored). Sync back to plot:
+#   rsync -avz hpc:'…/LamarckianAI/results/llm_directed_hpc/' results/llm_directed_hpc/
+echo "done: $(date)"