The Science of AI Detection: Burstiness & Perplexity
How do ZeroGPT, Winston, and Turnitin actually know a machine wrote your essay? It all comes down to two mathematical signatures.
To the naked eye, AI text looks perfect. To a detection algorithm, it looks like a mathematical pattern. To stay invisible, you need to understand the "Turing fingerprints" that Large Language Models (LLMs) leave behind. These are categorized into two primary metrics.
Perplexity
This measures the randomness of the text. AI predicts the most statistically probable next word. Humans choose words that are unexpected but contextually rich. Low perplexity is the biggest red flag for detectors.
Burstiness
This measures the variation in sentence structure. AI is a metronome—it maintains a steady, predictable rhythm. Humans write in "bursts": a long, detailed sentence followed by a short, sharp one. High variation is uniquely human.
Mathematical Signature Comparison
How NaturizeAI Fixes the Science
Our neural humanizer doesn't just swap synonyms. It performs Contextual Rerouting. By analyzing the perplexity score of every sentence in real-time, Naturize manually "upsets" the statistical probability of the text.
We inject unpredictable linguistic nodes and force structural variation, effectively mimicking the chaotic, high-complexity signature of a human brain at work.
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