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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
GPT-5.4
openrouter
9.60
WINNER SCORE
matrix avg: 9.35
results.json report.mdFull dataset (CSV) →
10×10 Judgment Matrix · 88 judgments
OPEN DATA
Judge ↓ / Respondent →Gemini 3.1 ProClaude Opus 4.6GPT-5.4DeepSeek V4MiMo-V2-FlashClaude Sonnet 4.6Grok 4.20GPT-OSS-120BGemini 3MiniMax M2.5
Gemini 3.1 Pro10.010.010.010.010.010.010.010.010.0
Claude Opus 4.69.210.09.210.010.010.010.09.49.8
GPT-5.48.39.68.69.69.69.68.68.28.8
DeepSeek V49.09.29.210.09.79.49.79.49.0
MiMo-V2-Flash9.29.49.49.410.010.09.39.49.0
Claude Sonnet 4.69.09.610.08.89.610.09.69.09.2
Grok 4.208.89.09.28.88.89.0·8.88.8
GPT-OSS-120B8.49.2·8.68.88.48.48.08.7
Gemini 39.610.010.09.810.010.010.010.09.8
MiniMax M2.58.69.09.09.09.29.28.89.08.6