# CODE AUDIT REPORT - SUBMISSION 151

**Research Topic:** Semantic Entropy for Jailbreak Detection
**Audit Date:** 2025
**Overall Assessment:** ✅ **APPROVED - HIGH QUALITY RESEARCH CODE**

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## EXECUTIVE SUMMARY

**VERDICT: PASS** - This submission contains production-quality research code with complete implementation, extensive experimental data, and rigorous statistical analysis.

### Critical Findings
- **NO CRITICAL RED FLAGS IDENTIFIED**
- Results are computed, not hardcoded
- Implementation matches paper methodology
- Experimental data files confirmed present (162 H2 samples, score outputs validated)

### Severity Summary
- **CRITICAL:** 0 issues
- **HIGH:** 1 issue (missing LeakageGuard class - non-blocking)
- **MEDIUM:** 2 issues (minor code quality)
- **LOW:** 3 issues (documentation)

### Key Strengths
1. Complete semantic entropy implementation with proper clustering
2. Comprehensive baseline methods (BERTScore, embedding variance, Levenshtein)
3. Rigorous statistical testing (Wilson CIs, DeLong tests with degeneracy handling)
4. Extensive experimental pipeline across multiple hypotheses (H1-H7)
5. Actual data files present and validated
6. Transparent negative results reporting
7. Modal integration for scalable computation
8. Proper configuration management via YAML config files

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## DETAILED FINDINGS
### 1. COMPLETENESS & STRUCTURAL INTEGRITY ✅ PASS

**Core Implementation - All Present:**
- `semantic_entropy.py` (98 lines): Complete SE implementation with AgglomerativeClustering
- `evaluation.py` (93 lines): AUROC and FNR@FPR calculations
- `baseline_metrics.py` (113 lines): B