lv-mccarthy D3 on gx10: leak gate PASSED, and the val split is now bigger than Hemingway's

~/lv-mccarthy on pfi-gx10: corpus-clean, corpus-renamed (6 copies, 1,002 records), scripts.

  leak gate   0 of 75 renameable and 0 of 37 sub-threshold survive in any copy
              positive control 108/108 surfaces found in the unrenamed source
              negative control nonce absent from both trees

THREE McCARTHY-SPECIFIC DECISIONS, each forced by a measurement.

1. --scope corpus, NOT the default per-work map. The Border Trilogy shares characters
   across books -- 9 surfaces appear in more than one work, including Parham (The
   Crossing + Cities of the Plain), Grady and Cole (All the Pretty Horses + Cities of
   the Plain), Socorro and Héctor. A per-work map would give John Grady a different
   invented name in each novel, turning one character into two.

2. A NEW `mccarthy` rename preset rather than reusing `hemingway`. Both are
   Spanish-inflected, but Hemingway's romance pool carries it_IT and fr_FR for his
   Italian and French casts, and McCarthy writes neither language -- drawing from it
   would drop Italian and French surnames into a Texas-Mexico border novel. en_GB goes
   for the same reason. en_US + es_MX/es_ES at an even share.

3. --min-cap 5 to MATCH the entity map's floor. The first gate run FAILED with 45
   survivors, and the diagnosis is the Brontë lesson exactly: entities.py admits
   cap >= 5 while rename.py only renamed cap >= 8, so every entity between 5 and 7 sat
   in the map, was never renamed, and was counted as a leak. Hemingway never hit it
   because its map had sub_threshold_total 0.

⭐ --holdout-chapter NOW TAKES A LIST, and this is the change with the most downstream
effect. The val split is one chapter index per work, so its SIZE is set by how many
WORKS a corpus has, not how many words:

  Hemingway  10 works -> 9 val units -> 36,563 words/copy -> gate DECISIVE
  Brontë      4 works -> 4 val units -> 17,043 words/copy -> gate MARGINAL
  McCarthy    6 works -> 6 val units -> ~18,000 would have been Brontë's end of that

Holding out chapters 7 AND 17 gives 11 units and 40,653 words per copy -- larger than
Hemingway's, at a cost of 7% of the corpus -- on a corpus 40% smaller than his. No
amount of corpus size fixes a val split that scales with work count.

THE HUMAN GENDER PASS IS NOW AN AUDITABLE FILE, not a hand edit. The honorific/window
resolver scored 21 correct / 3 held / 1 WRONG against a 26-name control; the base-rate
proximity resolver built for Hemingway scored 18/6/1 and its own guard correctly
REFUSED to write. So the incumbent stands and four entries are fixed by hand in
gender_overrides_mccarthy.json, each carrying its evidence.

⚠ All four are female and all four look male-dominated in raw pronoun counts, because
this corpus runs 29,144 male pronouns to 5,036 female -- a base rate of 85.3% male.
Carla Jean Moss at 31m/21f would be 44m/8f at that base rate, so 21 female against an
expected 8 is decisive. Same arithmetic that recovered Pilar and Brett on Hemingway.
Alfonsa was in my control set and is correctly absent from the map at 4 occurrences,
below the min-count floor -- an error in the control, not the pipeline.

apply_gender_overrides.py refuses two ways: a name absent from the map is an error
rather than a silent no-op, and overruling a gender the detector already holds needs
an explicit "correcting": true so it cannot look like filling a held entity in a diff.

scripts/mccarthy-corpus/gender_overrides_mccarthy.json

@@ -0,0 +1,34 @@
+{
+  "_why": [
+    "The human pass entities.py asks for. The honorific/window resolver scored 21 correct,",
+    "3 held and 1 WRONG against a 26-name hand-verified control; the base-rate proximity",
+    "resolver built for Hemingway scored 18/6/1 on the same control and its own guard",
+    "REFUSED to write, correctly. So the incumbent stands and these four are fixed by hand.",
+    "",
+    "⚠ Every entry below is FEMALE, and every one looks male-dominated in raw pronoun counts.",
+    "The McCarthy corpus runs 29,144 male pronouns to 5,036 female — a base rate of 85.3%",
+    "male. Against that background each of these is a strong female signal, which is the",
+    "same arithmetic that recovered Pilar and Brett on Hemingway.",
+    "",
+    "Alfonsa was in the control set and is NOT here: she appears 4 times, below the",
+    "--min-count 5 detection floor, so she is correctly absent from the map. That was an",
+    "error in the control, not in the pipeline."
+  ],
+  "Carla": {
+    "gender": "f",
+    "correcting": true,
+    "why": "Carla Jean Moss, Llewelyn's wife in No Country for Old Men. Read MALE by the incumbent because her scenes are dominated by Moss, Chigurh and Bell. Nearby pronouns 31m/21f — at the corpus base rate that would be 44m/8f, so 21 female against an expected 8 is decisive."
+  },
+  "Magdalena": {
+    "gender": "f",
+    "why": "The girl John Grady loves in Cities of the Plain. HELD by the incumbent. Nearby pronouns 17m/22f — a female MAJORITY inside an 85%-male corpus."
+  },
+  "Socorro": {
+    "gender": "f",
+    "why": "The cook at Mac's ranch — 'Socorro came and took the plate of biscuits and carried them to the oven'. HELD by the incumbent. Nearby pronouns 80m/65f against an expected 124m/21f."
+  },
+  "Luisa": {
+    "gender": "f",
+    "why": "A servant in Cities of the Plain — 'Luisa had gone to bed and the house was quiet'. HELD by the incumbent. Nearby pronouns 13m/10f against an expected 20m/3f."
+  }
+}