Automated LLM-driven hypothesis generation and testing on tabular datasets. Use when you want to systematically explore hypotheses about patterns in empirical data (e.g., deception detection, content analysis). Combines literature insights with data-driven hypothesis testing. For manual hypothesis formulation use hypothesis-generation; for creative ideation use scientific-brainstorming.

基于自动化大型语言模型的表格数据假设生成与验证。适用于系统性探索经验数据中模式的假设（例如，欺骗检测、内容分析）。结合文献洞察与数据驱动的假设检验。如需手动提出假设，请使用“假设生成”；如需创意构思，请使用“科学头脑风暴”。