…PMAT-CODE-SHIP-005-R1-R2-REFINEMENT)

§67 identified four refinement candidates for the SHIP-005 4.31pp
residual gap (80.49% → 84.80% floor). This PR ships R1+R2.

R1: multi-block extraction. The model sometimes emits an
explanatory snippet block BEFORE the actual solution block. The
prior first-block-wins extractor returned the snippet; this PR
scans ALL blocks.

R2: function-targeted extraction. When `entry_point` is supplied,
prefer the fenced block whose body contains `def {entry_point}(`.
This anchors extraction to the intended solution function rather
than relying on block ordering.

Fallback: when no block contains the entry_point (or none has the
target function), return the first non-empty block — preserving
the legacy `extract_python_code_block` behaviour as a strict
superset.

Implementation:
- NEW `extract_python_code_block_targeted(text, entry_point) -> Option<String>`
- `extract_python_code_block(text)` is now a thin wrapper that
  calls the targeted variant with `None` (backwards-compatible)
- `run_humaneval_inference` passes `Some(entry)` so HumanEval
  evaluations always use function-targeted extraction

Unit tests (7 new + 6 legacy = 13 GREEN):
- prefers_block_containing_entry_point (R2 canonical)
- single_block_matching_entry
- no_entry_match_falls_back_to_first (R2 robustness)
- no_entry_point_first_block_wins (legacy compat)
- mixed_fence_tags_picks_entry_block (R1+R2 combined)
- no_fence_returns_none
- skips_empty_fences_before_match
- (+ 6 legacy extract_python_code_block_tests still passing)

Five-Whys:
1. Why R1+R2? §67 identified 4 refinement candidates; R1+R2 are
   cheapest (extraction-only, no compute beyond rerun).
2. Why both together? They share the same multi-pass parser
   refactor; splitting them would be artificial.
3. Why not also R3 (Q4K → FP16)? Different artifact (needs
   safetensors); separate cascade.
4. Why not R4 (temperature sampling)? Larger compute footprint
   (3 samples × 164 problems × ~125s ≈ 17h on gx10). R1+R2 is
   the higher-leverage single-PR win.
5. Why ship as robustness even if smoke test shows it doesn't
   flip the 3 hardest failures (1, 3, 6)? Unit tests prove
   correctness on multi-block scenarios. The 4.31pp gap may
   require R3 or R4 to fully close, but R1+R2 is the necessary
   robustness baseline for any future eval.

LIVE smoke (gx10 3 problems known-failed pre-fix):
- HumanEval/1 (separate_paren_groups): FAIL (unchanged — model
  emits single block; the failure is model-quality at greedy
  temp=0, not extraction)
- HumanEval/3 (below_zero): FAIL (unchanged)
- HumanEval/6 (parse_nested_parens): FAIL (unchanged — also
  failed in PR #1628 5-problem smoke; hardest problem in the set)

These three are NOT extraction failures; they're greedy-sampling
or Q4K-quantization failures. R3/R4 may flip some. R1+R2 is the
robustness baseline.

A full 164-run on gx10 to measure R1+R2's exact gain is dispatchable
as a follow-up. Expected gain: 0-3pp depending on how many of the
32 failed problems were extraction failures vs sampling failures.

Validation:
- cargo test -p apr-cli --release --features cuda
  extract_python_code_block → 13/13 pass (7 new + 6 legacy)
- cargo build -p apr-cli --release --features cuda (gx10 aarch64):
  clean
- 3-problem LIVE smoke: confirms robust extraction (no regression)

Spec movement:
- MODEL-1 ship %: stays at 94% (no LIVE-discharge from this PR;
  may flip post-full-164 if R1+R2 closes ≥4.31pp)
- MODEL-2 ship %: unchanged at 57%

Refs:
- SPEC-SHIP-TWO-001 §66 (H4 confirmation)
- SPEC-SHIP-TWO-001 §67 (H4 result + R1-R4 scope)
- PR #1628 (H4 fix — base of this refinement)

Closes task #44 PMAT-CODE-SHIP-005-R1-R2-REFINEMENT.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>