u/Either_Pound1986 — reddlx

I put together a small Hugging Face Space for exploring public-source reports of mystery / unidentified / suspicious / unauthorized drone activity around sensitive locations.

Link: https://huggingface.co/spaces/cjc0013/dronesightings

It currently has 149 public-source report cases with source links, dates, country/region, site signals, evidence tiers, and plain-language caveats.

Important boundary: this is not claiming these are anomalous, NHI, hostile, or even definitely drones in every case. It is a review index / triage map. The point is to make it easier to see patterns, find source links, and separate stronger cases from weaker leads.

The dataset splits rows into rough evidence tiers:

resolved sensitive-site reports
named sensitive-site reports needing follow-up
broader source-discovered reports

The places include contexts like military sites, airports, maritime areas, emergency-service contexts, and critical infrastructure.

I built it because a lot of drone/UAP discussion gets stuck in scattered articles, screenshots, and one-off reports. This is meant to be a cleaner starting point for people who want to inspect the sources directly.

Would be interested in feedback from this sub, especially:

obvious missing cases
bad rows that should be removed
better source links
official statements / NOTAMs / police or military releases that can harden a case
better ways to classify “strong” vs “weak” reports

Again: not presenting this as proof of anything exotic. It is a public-source map for reviewing the reports more systematically.

I built a public-source evidence surface to test one narrow UAP claim:

Do public UFO/UAP report rows cluster near nuclear power plants?

This is not a truth claim about any specific sighting. It is only a geography/proximity test using public report rows, Census place population, major airport proximity, and matched non-nuclear power plant controls.

The result surprised me a bit:

The nuclear-specific proximity claim did not hold in this dataset.

Primary 50-mile test:

Public geocoded report rows: 105,250
Nuclear power-plant sites: 57
Matched non-nuclear power-plant controls: 285
Mean reports within 50 miles of nuclear sites: 649.98
Mean reports within 50 miles of matched non-nuclear controls: 763.05
Nuclear/control ratio: 0.851823
One-sided p-value for nuclear > controls: 0.854146

So in this reduced public dataset, nuclear sites did not show a stronger report-density signal than matched non-nuclear power sites.

The stronger visible pattern was reporting geography.

Population mattered a lot:

105,086 of 105,250 geocoded rows matched to Census population places
log population vs. log report-count correlation: 0.641288

Airport proximity was also measurable, but it mostly followed population geography:

Median report-row distance to a major scheduled airport: 13.277 miles
Population-weighted Census-place median: 10.764 miles

So airport proximity looks like a confounder, not a clean standalone explanation.

Important limits:

This does not prove any sighting is true or false.
This does not prove aircraft explain every report.
This does not test classified military/nuclear weapons sites.
This uses Census place centroids, not exact witness GPS.
17,783 U.S. rows did not resolve cleanly to Census place centroids and were excluded from spatial tests until recovered.

What I think this shows:

Public UAP report geography is heavily shaped by where people live, report, and have open sky visibility. If someone wants to argue for a nuclear-specific signal, the comparison needs matched controls, not just “there are reports near nuclear sites.”

This was built as an evidence surface, not a conclusion machine. The useful part is that every claim stays bounded: what the public data supports, what it does not support, and what needs another run.

HF space link: please let me know if you see anything wrong, or if I can add in any tests, using public data only.

https://huggingface.co/spaces/cjc0013/nuclear-uap-evidence-surface