# Scaiences

**AI for life sciences research.**

## The Vision

To cure cancer, end aging, and solve biology's hardest problems, we need more than human researchers. We need an **AI Scientist**.

**We use LLMs to synthesize the literature, generate hypotheses, and see patterns at a scale no single researcher could.**

Scaiences is the beginning of our effort to make that happen.

## Phase 1: Certainty

Before an AI can reliably generate hypotheses or plan experiments, it must understand evidence.
Current models are confident, but often hallucinate. Science requires **certainty**, not just confidence.

**We are conducting an overview of reviews (umbrella review) to map the existing evidence.**

> **Synthesize before you hypothesize.**

The field is moving fast, and many reviews already exist. Instead of reinventing the wheel, we are consolidating review-level evidence to separate durable lessons from hype.

Our specific focus:
*   **Consensus**: Where is the evidence strongest?
*   **Evaluation**: Which methods (calibration, traceability) are robust?
*   **Gaps**: What failure modes are consistently reported?

## Contributing

This is an open research project from day one. We are building benchmarks, datasets, and baseline models transparently.

If you are interested in evidence synthesis, biomedical NLP, or the future of automated science, join us.