AI Watermark & Research Integrity Inspector

Kirchenbauer-Anthropic Engine

Sequence Partition & Token Diagnostics

Interactive Token Partition Map (● Green List | ● Red List): 45 Tokens
Token: Recent
Idx: 0
Hash Seed (h): 0x8f2a1b
Partition: Green List (Accepted)
Logit Shift: +2.00
Perturbation & Paraphrase Stress-Tester 0% Signal Decay

Null Hypothesis Detection Test (z-Score)

H₀: Human text vs H₁: Watermarked
High Confidence Watermarked
Green token frequency exceeds Gaussian null expectation at α = 0.01.
p = 2.85e-05
Observed z-Score 4.0249 Critical z_α: 2.3263
Green Ratio (|G|/T) 80.0% 36 / 45 Tokens
False Positive Risk 0.003% 1 in ~35,000 papers
Null Hypothesis Normal Distribution N(0,1):
Academic Integrity Note: Low-entropy boilerplate text (e.g. standard chemical synthesis protocols or mathematical equations) naturally constrains vocabulary, increasing false positive probabilities under uncalibrated watermarking thresholds.
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