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HypoGeniC
维护者 K-Dense Inc. · 最近更新 2026年4月1日
HypoGeniC:Hypogenic provides automated hypothesis generation 、 testing ,使用 large language models to accelerate scientific discovery。 框架 supports three approaches:HypoGeniC (data-driven hypothesis generation),HypoRefine (synergistic literature 、 data integration),、 Union methods (mechanistic combination of literature 、 data-driven hypotheses)。
原始来源
K-Dense-AI/claude-scientific-skills
https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/hypogenic
- 维护者
- K-Dense Inc.
- 许可
- MIT license
- 最近更新
- 2026年4月1日
技能摘要
来自 SKILL.md 的关键信息
核心说明
- Hypogenic provides automated hypothesis generation 、 testing ,使用 large language models to accelerate scientific discovery. 框架 supports three approaches:HypoGeniC (data-driven hypothesis generation),HypoRefine (synergistic literature 、 data integration),、 Union methods (mechanistic combination of literature 、 data-driven hypotheses)。
- uv pip install hypogenic。
原始文档
SKILL.md 摘录
Quick Start
Get started with Hypogenic in minutes:
## Clone example datasets
git clone https://github.com/ChicagoHAI/HypoGeniC-datasets.git ./data
## Run basic hypothesis generation
hypogenic_generation --config ./data/your_task/config.yaml --method hypogenic --num_hypotheses 20
适用场景
- Generating scientific hypotheses ,面向 observational 数据集s。
- Testing multiple competing hypotheses systematically。
- Combining literature insights ,支持 empirical patterns。
- Accelerating research discovery through automated hypothesis ideation。
不适用场景
- Do not rely on this catalog entry alone ,用于 installation 或 maintenance details。
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