hypogenic

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• Hypogenic
• Overview
• Quick Start
• When to Use This Skill
• Key Features
• Core Capabilities
• 1. HypoGeniC: Data-Driven Hypothesis Generation
• 2. HypoRefine: Literature and Data Integration

Hypogenic provides automated hypothesis generation and testing using large language models to accelerate scientific discovery. The framework supports three approaches: HypoGeniC (data-driven hypothesis generation), HypoRefine (synergistic literature and data integration), and Union methods (mechanistic combination of literature and data-driven hypotheses). Get started with Hypogenic in minutes: Or use Python API: Use this skill when working on: Generating scientific hypotheses from observational datasets Testing multiple competing hypotheses systematically Combining literature insights with empirical patterns Accelerating research discovery through automated hypothesis ideation Domains requiring hypothesis-driven analysis: deception detection, AI-generated content identification, mental health indicators, predictive modeling, or other empirical research Automated Hypothesis Generation Generate 10-20+ testable hypotheses from data in minutes Iterative refinement based on validation performance Support for both API-based (OpenAI, Anthropic) and local LLMs Literature Integration Extract insights from research papers via PDF processing Combine theoretical foundations with empirical pat

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