zanekoch

zanekoch / airpods-go-brrrrr

Public

Cell phone radiofrequencies make mice & rats live longer

11
0
100% credibility
Found Mar 18, 2026 at 11 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Jupyter Notebook
AI Summary

This project re-analyzes U.S. government animal studies on cell phone radiofrequency radiation effects, sharing statistical insights on survival and disease risks with code to visualize results.

How It Works

1
📱 Wonder about cell phone safety

You hear scary news about cell phones maybe causing cancer and search for trustworthy animal study results.

2
🔍 Discover this helpful analysis

You find a clear project breaking down official government studies on radiation from phones like old 2G tech in mice and rats.

3
📖 Read the easy summary

You go through the friendly report explaining survival rates, tumor risks, and why some health changes might just mean animals lived longer.

4
📊 See the charts and numbers

You check out the tables and graphs showing no clear cancer rise in mice and one possible heart tumor signal in rats, adjusted for age.

5
💾 Grab the study files

You download the original animal health records from safe government links to explore the raw info yourself.

6
🖥️ Make your own pictures

You use the simple drawing tools to create graphs of disease trends and survival curves, matching the report's findings.

✅ Feel smart and calm

Now you understand these big studies show mostly no big risks from phone radiation, helping you use your devices worry-free.

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Star Growth

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AI-Generated Review

What is airpods-go-brrrrr?

This Python project reanalyzes raw data from US National Toxicology Program studies (TR-595 rats, TR-596 mice) on cell phone radiofrequency radiation at 1,900 MHz CDMA modulation. It runs Kaplan-Meier survival curves and logistic regressions on pathology outcomes, adjusting for sex and survival differences to test dose-response trends. Developers get reproducible scripts to load Excel data, compute odds ratios for neoplastic/non-neoplastic lesions, and generate forest plots showing exposed rodents often lived longer with fewer age-related diseases.

Why is it gaining traction?

Unlike summary-level github cell phone radiation repos or think cell github tools, it uses individual animal records for precise stats, revealing no cancer signals after confounder adjustment—flipping NTP's "equivocal" verdict. The hook: clear plots and tables expose survival benefits in high-dose groups, sparking debate on cell phone tower EMF effects amid cell phone location erfahrungen concerns. Jupyter-friendly with pandas, statsmodels, and lifelines for quick replication.

Who should use this?

Bioinformatics devs parsing toxicology datasets, EMF researchers validating cell phone drake-era 2G risks, or stats folks modeling survival in rodent studies. Ideal for virtual cell github experiments or github cell detection in pathology data.

Verdict

Skip unless you're deep in cell phone jammer or splinter cell github RF analysis—1.0% credibility score, 11 stars, and barebones docs signal early immaturity. Still, solid stats baseline for forking into robust tools. (187 words)

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