Discerning Scientific Innovation from Crankery

This brief, Discerning Scientific Innovation from Crankery, presents a practical framework for evaluating unconventional scientific work through a method-centered lens. It outlines core criteria—falsifiability, logical consistency, data engagement, and predictive capability—that distinguish legitimate scientific innovation from pseudoscientific claims. The goal is not to suppress nontraditional ideas but to assess them with clarity and rigor, independent of institutional authority or academic credentials.

The author utilizes AI as a tool to structure, refine, and communicate complex arguments more efficiently. While AI enhances productivity and expression, it requires its own learning curve—users must apply disciplined reasoning and critical oversight to ensure output quality. AI is not a substitute for rigor; it is a catalyst for more precise thought.