Generate and test data-driven hypotheses from tabular datasets with literature grounding.
npx skills add https://github.com/OwnLabAI/ownlab --skill hypogenic-ownlabai
Please help me install this Agent Skill. Skill: hypogenic Source: https://github.com/OwnLabAI/ownlab/tree/main/mart/skills/scientific-skills/hypogenic Command: npx skills add https://github.com/OwnLabAI/ownlab --skill hypogenic-ownlabai
Hypogenic helps researchers systematically generate and test hypotheses by combining data-driven insights with literature grounding, accelerating scientific discovery and validation.
Install Hypogenic, point it at your dataset, and run a basic generate-and-infer workflow to produce and evaluate hypotheses.
High-intent search queries and answers about installing and using this skill.
Data-driven hypothesis generation automates systematic exploration by integrating your observational datasets with scholarly literature to produce and evaluate testable hypotheses. It supports configurable prompts and scalable inference for large-scale experiments.
Yes, literature-informed hypothesis refinement grounds generated ideas in existing research. The workflow integrates scholarly references to systematically refine and validate testable hypotheses across multiple domains.
The best way to scale hypothesis testing uses an end-to-end workflow with caching for efficient large-scale experiments. It supports API or local model support and configurable prompts to handle large observational datasets.
Yes, the hypothesis generation workflow supports both API and local LLM models. It uses configurable prompts and templates to automate inference, allowing you to systematically generate and evaluate testable hypotheses.
You systematically test hypotheses using an end-to-end workflow that includes hypothesis inference and evaluation. By pointing the workflow at your tabular datasets, it automates the generate-and-infer process to produce and evaluate hypotheses.
jaechang-hitsGenerate and test scientific hypotheses on labeled tabular datasets using LLMs.
HolobiomicsLabGenerate structured mechanistic hypotheses with testable predictions and appendices.
qinyan-aiEvaluate scholarly work with weighted dimension scores via calculate_scores.py.
wachawoProfile dataset structure, completeness, and statistical validity with pandas and numpy.
