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@@ -18,12 +18,18 @@ generators (GPT-4o, Gemini 2.5, Groq Llama, Cerebras Llama).
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  We release the full calibration corpus, evaluation harness, regression test
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  suite, and a 300-sample held-out adversarial corpus produced via
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- cross-model single-pass paraphrasing. On a 44-text hand-curated
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- out-of-distribution smoke battery, our v1.11 ensemble achieves AUROC
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- **0.821 (English)** and **0.837 (Russian)**, with English Wrong-rate
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- of 4% and median latency of 1.2 seconds on commodity 8-vCPU hardware. On
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- the 300-sample adversarial paired set, ensemble AUROC reaches **0.985** (in-
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- distribution human baseline).
 
 
 
 
 
 
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  The contribution of this work is **field-leading reproducibility**, not
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  state-of-the-art absolute AUROC. Anyone can clone the repository, run the
@@ -73,11 +79,16 @@ with a five-feature text-level structural head. We release:
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  Our headline numbers, reproducible end-to-end on Hetzner CX43-class hardware
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  ($25/month) within 90 minutes:
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- - **English ensemble OOD AUROC: 0.802** (44-text smoke, post-Gap-7-tuning)
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- - **Russian ensemble OOD AUROC: 0.847**
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  - **English ensemble adversarial AUROC: 0.984** on 300-sample paraphrase-paired set
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  - **English ensemble p50 latency: 1.2 seconds** (8-core CPU, no GPU)
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  The first three numbers are competitive with the best peer-reviewed
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  commercial figures while remaining honestly reported on OOD and adversarial
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  evaluations. The fourth—latency—was achieved by removing Binoculars from
 
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  We release the full calibration corpus, evaluation harness, regression test
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  suite, and a 300-sample held-out adversarial corpus produced via
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+ cross-model single-pass paraphrasing.
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+
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+ **Headline numbers v1.11 ensemble on 176-sample expanded smoke battery
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+ (2026-04-29 measurement):** AUROC **0.864 (English)** and **0.846
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+ (Russian)**, with English Wrong-rate of 4% and median latency of 1.2
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+ seconds on commodity 8-vCPU hardware. Earlier 44-text hand-curated
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+ smoke (v1.0 paper measurement) reported 0.821 EN / 0.837 RU; the
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+ 4× expanded battery with proper class balance per (lang, genre) cell
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+ stabilized the numbers upward.
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+
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+ On the 300-sample adversarial paired set, ensemble AUROC reaches
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+ **0.985** (in-distribution human baseline).
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  The contribution of this work is **field-leading reproducibility**, not
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  state-of-the-art absolute AUROC. Anyone can clone the repository, run the
 
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  Our headline numbers, reproducible end-to-end on Hetzner CX43-class hardware
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  ($25/month) within 90 minutes:
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+ - **English ensemble OOD AUROC: 0.864** (176-sample expanded smoke, 2026-04-29)
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+ - **Russian ensemble OOD AUROC: 0.846** (176-sample expanded smoke, 2026-04-29)
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  - **English ensemble adversarial AUROC: 0.984** on 300-sample paraphrase-paired set
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  - **English ensemble p50 latency: 1.2 seconds** (8-core CPU, no GPU)
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+ Earlier v1.0 paper reported 0.802/0.847 on the original 44-text smoke;
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+ the expanded 176-sample battery with class balance per (lang, genre) cell
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+ revealed that several "weak slots" at small n_h were sample-size noise,
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+ and stabilized values upward.
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+
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  The first three numbers are competitive with the best peer-reviewed
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  commercial figures while remaining honestly reported on OOD and adversarial
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  evaluations. The fourth—latency—was achieved by removing Binoculars from