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analysis
Jan 15, 2026ANALYSIS-001

Critique this research abstract. Identify methodological issues, unsupported claims, and potential biases: "Our groundbreaking study proves that AI-generated code is 47% more efficient than human-written code. We analyzed 500 code snippets from GitHub (human) and ChatGPT (AI) across 10 programming languages. Our expert panel of 3 reviewers rated each snippet on efficiency, readability, and correctness. Results showed AI code scored significantly higher (p < 0.05) on all metrics. We conclude that AI should replace human programmers for all coding tasks. Limitations: Our reviewers knew which code was AI-generated." List every issue you find with this methodology and conclusions.

Winner
Claude Sonnet 4.6
openrouter
9.51
WINNER SCORE
matrix avg: 9.25
results.json report.mdFull dataset (CSV) →
10×10 Judgment Matrix · 89 judgments
OPEN DATA
Judge ↓ / Respondent →MiMo-V2-FlashGemini 3.1 ProClaude Opus 4.6GPT-5.4DeepSeek V4Claude Sonnet 4.6Grok 4.20GPT-OSS-120BGemini 3MiniMax M2.5
MiMo-V2-Flash8.89.69.29.610.09.69.39.68.8
Gemini 3.1 Pro10.010.09.410.0·10.09.310.010.0
Claude Opus 4.610.09.010.09.210.010.010.09.49.4
GPT-5.48.66.99.28.69.69.68.38.69.6
DeepSeek V49.28.89.79.29.79.09.49.49.0
Claude Sonnet 4.69.69.09.69.88.810.09.49.29.0
Grok 4.208.88.88.89.08.89.09.08.88.8
GPT-OSS-120B8.48.38.48.88.48.88.48.38.7
Gemini 310.09.610.010.09.810.010.09.89.8
MiniMax M2.59.48.49.29.08.89.09.09.28.8