# Nuclear/UAP Explanatory Factors Private Preview The better explanation surface is population/reporting geography plus ordinary aviation proximity, while the nuclear-specific proximity claim remains unsupported after controls. ## What changed - Missing geocodes are counted and routed; they are not silently filled. - Population and major-airport proximity are measured as confounders. - The previous nuclear matched-control test is carried forward as the nuclear-specific check. ## Strongest explanations we can support - Population explanation strength score: 78/100. - Airport confounder strength score: 90/100. - Nuclear non-support strength score: 95/100. - Place-level log(population) vs log(report count) correlation: 0.641288. - Events matched to Census population rows: 105086 of 105250. - Median event distance to a major scheduled airport: 13.277 miles. - Population-weighted median place distance to a major scheduled airport: 10.764 miles. ## Missing geocodes - Total U.S. rows scanned: 123013. - Rows without Census-place geocode: 17783 (0.144562). - These rows need county, landmark, route, relative-place, or fuzzy public-gazetteer recovery before entering spatial tests. ## What We Can Claim - The missing NUFORC-derived rows were not geocoded by assumption; they were excluded from spatial tests and logged for recovery. - The public geocoded report rows can be compared against Census place population and commercial-airport proximity as explanatory covariates. - At the place level, report counts can be assessed against population concentration without claiming reports are true or false. - Airport proximity can be treated as a public-source confounder, not as proof that airplanes caused specific reports. - The nuclear power-plant proximity claim remains unsupported in this evidence surface after matched non-nuclear power-plant controls. ## What We Cannot Claim - This dataset cannot prove what witnesses saw. - This dataset cannot claim aircraft explain every report. - This dataset cannot treat city/place centroids as exact sighting coordinates. - This dataset cannot rule out all nuclear-weapons, military, or classified-site hypotheses. - This dataset cannot assume the skipped missing-geocode rows would preserve or reverse the result without a separate recovery run.