Yang Chen (@chenyang03.bsky.social)

Helix 1.0: An open-source framework for reproducible and interpretable machine learning on tabular scientific data Helix is an open-source, FAIR-by-design analytics framework to address the growing need for transparency, interpretability, and reproducibility in data-driven scientific research. Designed for tabular data, Helix integrates the full analytical life cycle within a single modular, extensible environment. Helix places experimental provenance and human interpretability at its core, ensuring that modeling decisions, data transformations, and analytical outcomes are fully traceable and accessible. Its lightweight, browser-based interface lowers technical barriers for domain scientists while preserving methodological rigor and flexibility. http://dlvr.it/TRq7dB