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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-OSS-120B
OpenAI
9.82
WINNER SCORE
matrix avg: 9.69
↓ results.json↓ report.mdFull dataset (CSV) →
10×10 Judgment Matrix · 100 judgments
OPEN DATA
Judge ↓ / Respondent →MiMo-V2-FlashGPT-OSS-LegalGemini 3Gemini 2.5 FlashGPT-OSS-120BDeepSeek V3.2Claude Sonnet 4.5Claude Opus 4.5Gemini 3Grok 4.1 Fast
MiMo-V2-Flash—9.39.810.09.310.09.69.69.39.6
GPT-OSS-Legal0.0—0.00.00.00.00.00.00.09.0
Gemini 310.010.0—10.010.010.010.010.09.610.0
Gemini 2.5 Flash10.010.010.0—10.010.010.010.010.010.0
GPT-OSS-120B8.49.08.38.8—8.68.88.78.68.7
DeepSeek V3.29.89.49.610.010.0—10.010.09.39.1
Claude Sonnet 4.510.010.010.010.010.010.0—10.010.010.0
Claude Opus 4.510.09.49.49.29.49.89.8—9.29.8
Gemini 310.00.010.010.00.010.00.010.0—0.0
Grok 4.1 Fast10.09.810.010.010.010.010.010.09.8—