Dr. Grey: making research easier to inspect.

An interface for uncertainty

The difficult product question is what to simplify. A reader needs a useful starting point, but an attractive summary can create more certainty than its sources justify. I am interested in the space between an overwhelming set of papers and an answer that hides all the detail.

My role here is product and engineering. This is not a claim to medical authorship or clinical review, and my technology work does not validate a health claim.

What the product exposes

The public product organizes supplement and condition research around reported outcomes. Its methodology describes PubMed-indexed sources, links to research papers, and A–D evidence grades. These are navigation and explanation mechanisms; a grade is not a personalized treatment recommendation.

The engineering behind an evidence interface

The local implementation uses a Next.js application over a SQLite-backed research dataset. It has explicit representations for citations, outcomes, and research metrics. That creates a practical engineering obligation: a detail page, a directory summary, and a search result should not silently tell different stories about the same underlying data.

The direction is a shared research read model rather than disconnected summaries. Source projection, grade aggregation, and page presentation need to agree. These are software consistency concerns, separate from whether a study or a grading method is scientifically sound.

• Keep a displayed statement connected to the evidence record it summarizes.
• Use consistent definitions for counts and grades across surfaces.
• Distinguish a citation, a study, and a clinical trial rather than treating the terms as interchangeable.
• Make uncertain or missing information visible instead of filling it with confident prose.

Where the boundary belongs

The public methodology explicitly notes incomplete research coverage, periodic updates, and an inability to account for individual circumstances. Those limitations belong near the experience, not only in a footer.

Clinical validation, named qualified review, and freshness of the underlying evidence are distinct responsibilities. This case study describes the product work; it does not certify that every grade or citation has been independently reviewed.

A real product, without invented impact numbers

The observable output is a public research-browsing experience and its methodology. I am not attaching patient outcomes, accuracy percentages, or audience-growth claims to it without supporting measurements.

I also used Dr. Grey as a subject in my LTX UGC production experiments. Those experiments taught me about speech, lip-sync, and take selection—not supplement efficacy. Keeping those two kinds of evidence separate is part of telling the project honestly.