数据与复现地理信息与遥感K-Dense-AI/claude-scientific-skills数据与复现
HY

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)。

Claude CodeOpenClawNanoClaw分析处理复现实验hypogenicmulti-omicspackagemulti-omics & ai agent frameworks

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

2 min

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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