AI-powered tools have become more common in scientific research and development, especially for predicting outcomes or suggesting possible experiments using datasets. However, most of these systems only work with limited types of data. They might rely on numbers from a few tests or chemical inputs, but that only scratches the surface. Human scientists bring much more to the table. In a lab, decisions are shaped by a mix of sources. Researchers consider published papers, past results, chemical be...