fix(datasets): anchored grade extraction + surface judge failures in generic llmjudge

[YuhaoLin2005]

Motivation

_generic_llmjudge_postprocess scans the judge's free-text reply for the first A/B anywhere in it. Judges routinely justify their verdict before stating it, so a reasoning sentence that merely contains a letter silently overrides the real grade ("As a judge, I considered the evidence carefully. The final grade is B." parses as A). Separately, when a judge fails to emit a usable grade (API error, truncation, no letter in the reply), the result degrades to 'unknown', which get_final_results folds into the accuracy denominator — indistinguishable from a genuine wrong answer. Related upstream reports: #1232, #2522, #2392.

The fix (two parts)

1. Anchored grade extraction (no regression)

Only a grade that is explicitly anchored is trusted: a cue word (grade, verdict, final answer) immediately followed by a connector (is / was / be / of / : / = / :=) and the letter. Everything else keeps the existing loose scan, so every judge reply that previously parsed still parses (zero recall regression, no silently-dropped samples).

Deliberate exclusions, each with a regression test:

• bare answer is not a cue — "the answer is A" names the option, not the grade;
• a connector is required — "grade A of this study" is a quality qualifier, not an assignment.

2. Judge failures are surfaced, not absorbed

get_final_results now counts judge failures separately (judge_error_count, plus a judge_error flag on each failing detail), while accuracy, accuracy_given_attempted, not_attempted_count, and friends keep their exact historical semantics (unknown still counts as not-attempted). A judge failure can no longer be silently read as a wrong answer.

Tests

tests/datasets/test_generic_llmjudge_postprocess.py — 13 cases covering anchored extraction, the anti-false-anchor contract, and the aggregation surface. Follows tests/TESTING_GUIDE.md conventions.

Impact on existing results

This fix changes how judge replies that contain an anchored grade are parsed:
previously such replies could be mis-parsed as the first letter appearing in the
judge's prose (often wrong); now the anchored grade wins. Replies with a single
letter, or with no conflicting prose letter, are parsed exactly as before, so
only previously-wrong results change — in the correct direction. accuracy,
accuracy_given_attempted, and not_attempted_count keep their exact
historical semantics; judge_error_count is a new, purely additive field.

Out of scope

• Connector-less verb forms ("I grade A") are deliberately not covered and
  continue to follow the legacy scan — adding them would reintroduce the
  qualifier false-positive the connector requirement exists to prevent.
• The same loose-scan logic is copy-pasted into MedXpertQA.py,
  medmcqa.py, supergpqa/supergpqa.py, and atlas/evaluation.py (each with
  its own _generic_llmjudge_postprocess / get_final_results). This PR keeps
  the diff focused on the canonical generic.py; a follow-up could apply the
  same anchored-extraction pattern to the copies.