diff --git a/docs/JOURNAL.md b/docs/JOURNAL.md
index 13a8715..de174e6 100644
--- a/docs/JOURNAL.md
+++ b/docs/JOURNAL.md
@@ -18,6 +18,39 @@ protocol. **Newest entries at the top.** Tag each entry with one or more of:
 
 ---
 
+## 2026-07-23 — MC grading was hard-capped at A–D, silently zeroing MMLU-Pro E–J  #mistake #fix #repro
+**Context:** issues #116 / #122 (filed independently, same root bug). RLPR routes its MMLU-Pro
+subset (`MMLUPro-1000_Avg2`) through the `mmlu`/`gpqa` choice grader in `orchestration/reward.py`.
+**Expected:** a correct answer grades 1.0 regardless of which option letter is gold.
+**Actual:** every item whose gold answer is **E–J scored 0.0 even when the model answered
+correctly** — a silently-wrong number, not a crash:
+```python
+for gold in ["A", "D", "E", "F", "J"]:
+    ref = {"ground_truth": gold, "source": "MMLUPro-1000_Avg2"}
+    print(gold, R.score_text("rlpr", f"The answer is ({gold}).", ref))
+# A 1.0 / D 1.0 / E 0.0 / F 0.0 / J 0.0
+```
+**Root cause:** the grader was written for 4-option MMLU/GPQA and hard-capped at A–D in **four**
+independent places, so **both** sides of the comparison failed for a ten-option item — the answer
+could neither be extracted nor the reference normalized: the five `_CHOICE_PATTERNS` captured
+`([A-D])`, `extract_choice_letter`'s last-line fallback matched `([A-D])`, and
+`_normalize_reference_letter` accepted only `{A,B,C,D}` / integer index `<= 3`. MMLU-Pro has up to
+**ten** options (A–J) and its gold answers spread across all ten letters, so a large fraction of
+that subset was unconditionally graded 0 — deflating measured accuracy and distorting the
+per-benchmark routing signal the coordinator is trained and evaluated on.
+**Fix / decision:** introduce a single `_CHOICE_ALPHABET = "ABCDEFGHIJ"` (plus a derived character
+class) and drive **all four** sites from it, so the alphabet cannot drift out of sync again. This is
+safe for the 4-option benchmarks: MMLU/GPQA gold answers are always A–D, so extracting a stray
+higher letter still cannot match a 4-option gold — no existing score can flip; widening only *adds*
+the ability to grade E–J. Added `tests/test_reward_choice_alphabet.py` (offline, pure stdlib): every
+letter A–J end-to-end on RLPR MMLU-Pro, letter **and** integer-index normalization across A–J, plus
+guards that MMLU/GPQA are unchanged, that a stray high letter cannot match a 4-option gold, and that
+the prose article `"A"` is still not read as a choice.
+**Follow-up:** the ten-option range is orthogonal to *which* letter wins when a model echoes the
+option list — that ordering bug is tracked separately in #124 (PR #217). If #217 lands first, its
+new trailing-standalone-letter fallback also needs to use `_CHOICE_LETTER_CLASS` rather than a fresh
+`[A-D]` literal, or the cap is silently reintroduced on that path.
+
 ## 2026-07-12 — code grader: add resource limits on top of the HOME/secrets fix  #security #decision
 **Context:** issue #71 — the code grader (`run_pass_at_1`) runs untrusted miner/LLM candidate code. The core secret-leak fix (isolated throwaway HOME/cwd, scrubbed env, `python -I`) already landed on main.
 **Finding:** main's sandbox closes the HOME/secrets exfiltration vector but has **no resource limits** — an untrusted candidate can still exhaust host memory or fork-bomb the eval box within its wall-clock timeout (verified: a 4 GiB `bytearray` allocation runs to completion and "passes" on main).
diff --git a/src/trinity/orchestration/reward.py b/src/trinity/orchestration/reward.py
index b1da624..24073d6 100644
--- a/src/trinity/orchestration/reward.py
+++ b/src/trinity/orchestration/reward.py
@@ -21,9 +21,10 @@
     Parse a JSON function-call payload and compare it against the ground-truth
     call schema stored in ``task.answer``.
 * ``mmlu`` / ``gpqa``
-    Extract a single multiple-choice letter ``A-D`` (robust to phrasings such
-    as ``"the answer is (B)"``, ``"B)"``, ``"B."``) and compare to
-    ``task.answer``.
+    Extract a single multiple-choice letter (robust to phrasings such as
+    ``"the answer is (B)"``, ``"B)"``, ``"B."``) and compare to ``task.answer``.
+    The alphabet spans ``A-J`` so RLPR's ten-option MMLU-Pro items are gradeable;
+    4-option benchmarks only ever use ``A-D``.
 * ``livecodebench`` / ``bigcodebench``
     Execute candidate code against the task's tests in a subprocess sandbox
     with a timeout (``run_pass_at_1``). Never ``exec`` untrusted code in
@@ -942,27 +943,42 @@ def _ref_to_str(reference: object) -> str:
 # Multiple choice: MMLU / GPQA
 # ---------------------------------------------------------------------------
 # Match in priority order. Earlier patterns are more explicit / trustworthy.
+# Choice alphabet for the multiple-choice grading path. MMLU/GPQA are 4-option
+# (A-D), but RLPR routes MMLU-Pro (`MMLUPro-1000_Avg2`) here and MMLU-Pro has up
+# to TEN options (A-J) — capping at A-D silently scored every correct E-J answer
+# 0.0. Widening is safe for the 4-option benchmarks: their gold answer is always
+# A-D, so extracting a stray higher letter still cannot match a 4-option gold.
+_CHOICE_ALPHABET: str = "ABCDEFGHIJ"
+_CHOICE_LETTER_CLASS: str = f"[{_CHOICE_ALPHABET[0]}-{_CHOICE_ALPHABET[-1]}]"
+
 _CHOICE_PATTERNS: tuple[re.Pattern[str], ...] = (
     # Require the captured letter to be followed by a delimiter or end-of-word,
     # so "the answer Beats..." does NOT match "B" (P2 review fix).
-    re.compile(r"answer\s*(?:is|:)?\s*\(?\s*([A-D])\s*(?:[\).:]|\b)(?![A-Za-z])", re.I),
-    re.compile(r"\\boxed\s*\{\s*\(?\s*([A-D])\s*\)?\s*\}", re.I),
-    re.compile(r"\bfinal\s+answer\s*[:=]?\s*\(?\s*([A-D])(?![A-Za-z])", re.I),
-    re.compile(r"\boption\s*\(?\s*([A-D])(?![A-Za-z])", re.I),
-    re.compile(r"^\s*\(?\s*([A-D])\s*[\).:]", re.M),
+    re.compile(
+        rf"answer\s*(?:is|:)?\s*\(?\s*({_CHOICE_LETTER_CLASS})\s*(?:[\).:]|\b)(?![A-Za-z])",
+        re.I,
+    ),
+    re.compile(rf"\\boxed\s*\{{\s*\(?\s*({_CHOICE_LETTER_CLASS})\s*\)?\s*\}}", re.I),
+    re.compile(rf"\bfinal\s+answer\s*[:=]?\s*\(?\s*({_CHOICE_LETTER_CLASS})(?![A-Za-z])", re.I),
+    re.compile(rf"\boption\s*\(?\s*({_CHOICE_LETTER_CLASS})(?![A-Za-z])", re.I),
+    re.compile(rf"^\s*\(?\s*({_CHOICE_LETTER_CLASS})\s*[\).:]", re.M),
 )
 
 
 def extract_choice_letter(text: str) -> str | None:
-    """Extract a single multiple-choice letter ``A``-``D`` from ``text``.
+    """Extract a single multiple-choice letter ``A``-``J`` from ``text``.
 
     Robust to common phrasings: ``"the answer is (B)"``, ``"Answer: C"``,
     ``"B)"``, ``"B."``, ``"\\boxed{D}"``, ``"Option A"``. Tries explicit
     answer-bearing patterns first; if none match, falls back to the **last**
-    standalone capital ``A``-``D`` token in the text (final answers usually come
+    standalone capital ``A``-``J`` token in the text (final answers usually come
     last). Letters embedded in words (e.g. the ``A`` in ``"And"``) are excluded
     by requiring word boundaries / delimiters.
 
+    The alphabet spans ``A``-``J`` (not just ``A``-``D``) because RLPR's MMLU-Pro
+    subset has up to ten options; 4-option benchmarks are unaffected since their
+    gold answer is always ``A``-``D``.
+
     Args:
         text: Arbitrary model output.
 
@@ -979,7 +995,7 @@ def extract_choice_letter(text: str) -> str | None:
     # it is essentially just the letter (e.g. "B", "(C)", "D."). This avoids the
     # English article "A" in prose like "A nice approach" being read as a choice.
     for line in reversed([ln.strip() for ln in text.splitlines() if ln.strip()]):
-        m = re.fullmatch(r"\(?\s*([A-D])\s*\)?[.:]?", line, re.I)
+        m = re.fullmatch(rf"\(?\s*({_CHOICE_LETTER_CLASS})\s*\)?[.:]?", line, re.I)
         if m:
             return m.group(1).upper()
         break  # only inspect the final non-empty line
@@ -998,11 +1014,14 @@ def _check_choice(candidate: str, reference: object) -> bool:
 
 
 def _normalize_reference_letter(reference: object) -> str | None:
-    """Coerce a reference answer to a single ``A``-``D`` letter.
+    """Coerce a reference answer to a single ``A``-``J`` letter.
 
     Accepts a letter string (``"B"``, ``"(B)"``) or a 0-based / 1-based integer
     index (``1`` -> ``"B"`` under 0-based; datasets vary, so a bare letter is
     preferred). Returns ``None`` if it cannot be resolved.
+
+    The alphabet spans ``A``-``J`` so RLPR's MMLU-Pro gold answers (up to ten
+    options) are representable; 4-option benchmarks only ever use ``A``-``D``.
     """
     if reference is None:
         return None
@@ -1011,12 +1030,12 @@ def _normalize_reference_letter(reference: object) -> str | None:
         if letter is not None:
             return letter
         s = reference.strip().upper()
-        return s if s in {"A", "B", "C", "D"} else None
+        return s if s in set(_CHOICE_ALPHABET) else None
     if isinstance(reference, bool):
         return None
     if isinstance(reference, int):
-        if 0 <= reference <= 3:
-            return "ABCD"[reference]
+        if 0 <= reference < len(_CHOICE_ALPHABET):
+            return _CHOICE_ALPHABET[reference]
         return None
     return None
 
diff --git a/tests/test_reward_choice_alphabet.py b/tests/test_reward_choice_alphabet.py
new file mode 100644
index 0000000..b918178
--- /dev/null
+++ b/tests/test_reward_choice_alphabet.py
@@ -0,0 +1,82 @@
+"""Offline tests for the A-J multiple-choice alphabet (#116 / #122).
+
+RLPR routes MMLU-Pro (`MMLUPro-1000_Avg2`) to the choice grader, and MMLU-Pro has
+up to ten options, but the grader was hard-capped at A-D: every correct E-J answer
+scored 0.0 — a silently-wrong number, not a crash. These tests pin the widened
+A-J alphabet and, just as importantly, that the genuinely 4-option benchmarks
+(MMLU / GPQA) are unaffected. Pure stdlib: no network / GPU / torch.
+"""
+from __future__ import annotations
+
+import pytest
+
+from trinity.orchestration import reward as R
+
+
+def _rlpr_ref(gold: str) -> dict:
+    return {"ground_truth": gold, "source": "MMLUPro-1000_Avg2"}
+
+
+# --------------------------------------------------------------------------- #
+# The bug: E-J were unrepresentable end-to-end
+# --------------------------------------------------------------------------- #
+@pytest.mark.parametrize("gold", list("ABCDEFGHIJ"))
+def test_rlpr_mmlu_pro_grades_every_letter(gold):
+    assert R.score_text("rlpr", f"The answer is ({gold}).", _rlpr_ref(gold)) == 1.0
+
+
+@pytest.mark.parametrize("gold", list("EFGHIJ"))
+def test_rlpr_mmlu_pro_still_rejects_wrong_letter(gold):
+    wrong = "A" if gold != "A" else "B"
+    assert R.score_text("rlpr", f"The answer is ({wrong}).", _rlpr_ref(gold)) == 0.0
+
+
+# --------------------------------------------------------------------------- #
+# Helpers
+# --------------------------------------------------------------------------- #
+@pytest.mark.parametrize("letter", list("ABCDEFGHIJ"))
+def test_extract_choice_letter_spans_a_to_j(letter):
+    assert R.extract_choice_letter(f"The answer is {letter}") == letter
+    assert R.extract_choice_letter(f"Final answer: ({letter})") == letter
+    assert R.extract_choice_letter(f"\\boxed{{{letter}}}") == letter
+
+
+@pytest.mark.parametrize("letter", list("ABCDEFGHIJ"))
+def test_normalize_reference_letter_spans_a_to_j(letter):
+    assert R._normalize_reference_letter(letter) == letter
+
+
+def test_normalize_reference_letter_integer_index():
+    assert R._normalize_reference_letter(0) == "A"
+    assert R._normalize_reference_letter(4) == "E"
+    assert R._normalize_reference_letter(9) == "J"
+    # Out of range stays unresolvable.
+    assert R._normalize_reference_letter(10) is None
+    assert R._normalize_reference_letter(-1) is None
+
+
+def test_normalize_reference_letter_rejects_non_choices():
+    assert R._normalize_reference_letter("Z") is None
+    assert R._normalize_reference_letter(None) is None
+    assert R._normalize_reference_letter(True) is None
+
+
+# --------------------------------------------------------------------------- #
+# Guards: the 4-option benchmarks must be unaffected
+# --------------------------------------------------------------------------- #
+def test_four_option_benchmarks_unchanged():
+    assert R.score_text("mmlu", "The answer is (B).", "B") == 1.0
+    assert R.score_text("mmlu", "The answer is (C).", "B") == 0.0
+    assert R.score_text("gpqa", "Answer: D", "D") == 1.0
+
+
+def test_stray_high_letter_cannot_match_four_option_gold():
+    # Widening only adds the ability to grade E-J; it can never flip a 4-option
+    # answer, because the gold there is always A-D.
+    assert R.score_text("mmlu", "The answer is (I).", "B") == 0.0
+    assert R.score_text("gpqa", "The answer is (J).", "A") == 0.0
+
+
+def test_prose_article_a_still_not_read_as_choice():
+    # The existing false-positive guard must survive the widened alphabet.
+    assert R.extract_choice_letter("A nice approach to think about it") is None