An AI text detector compares measurements from a passage with patterns learned from labeled examples. Its output depends on the examples, language, genre, length, preprocessing and release date. It is not a direct observation of authorship.
From text to a bounded comparison
- Extraction: preserve the submitted text, count coverage and record any truncation.
- Features: measure repetition, rhythm, vocabulary, syntax, mechanics and semantic progression without treating document length as origin evidence.
- Benchmark: compare only with the named human/model cells the release actually tested.
- Calibration: report held-out error, uncertainty and known drift rather than decorating a raw output as certainty.
- Abstention: withhold the number when length, language, coverage or formatting stability does not qualify.
Why this release withholds a combined number
AI Text Signals has not released an exact-stack, leakage-resistant held-out card for a combined T score. The local tool therefore shows descriptive measurements and eligibility, not an invented 0–100 probability. “No score” is a product result when the evidence cannot support one.
Three questions stay separate
T
Which writing patterns resemble a named benchmark?
P
What does the supplied page literally declare or expose?
Q
What could make the material clearer and easier to read?