Signal, not noise.

What this is

The Signal Report is a working scientist's read on science and world events. Each report takes one story — a paper making headlines, a new defense technology in the news, a supplement claim going viral — and separates what the evidence supports from what got added in the retelling. The name is the mission: in both electronic warfare and spectroscopy, the entire job is pulling signal out of noise. This is that job, applied to the news.

Who's writing

I'm Onur Oncer. I served as a U.S. Army Counter-IED and Electronic Warfare Officer, with a combat deployment to Afghanistan in 2011. After the Army I became a published researcher — my peer-reviewed work is in microwave spectroscopy, done in the Kukolich group at the University of Arizona. Since then I've managed an iPSC core lab, consulted on laboratory operations and AI, and founded Shroombiosis, a functional-mushroom supplement company. I've been the person generating the data, the person reviewing the claims, and the person selling the product — which is exactly why I hold claims to a high bar.

The method

• Primary sources only. Every factual claim links to the paper, dataset, or original document — with DOIs where they exist. If I can't source it, I say so or I don't print it.
• Claims stay hedged to the evidence. "Suggests" means suggests. A cell study is a cell study. A preprint is labeled a preprint.
• Corrections happen in place. If a report is wrong, it gets fixed where it stands, with a dated note saying what changed.
• No sponsors, no affiliates. Nothing here is paid for, and no link earns a commission. Where I have a stake — I formulate supplements — I'll flag it in the report.

The beat

• Defense tech, decoded. Drones, jamming, counter-IED, electronic warfare — what the technology in this week's headlines actually does, from someone who operated it.
• Lab science worth understanding. Spectroscopy, materials, cell biology — explainers on the methods behind the results, so the results make sense.
• Supplement-science reality checks. What a study measured versus what the marketing claims — dosing, models, and effect sizes, read honestly.
• AI in the lab. Where machine learning genuinely helps research and operations, and where it's expensive theater.

End of briefing

Report 002 is in the works. If you want reports as they land, the RSS feed is live — or write to me directly if there's a story you think deserves the treatment.