The single most useful fact: the asterisk
If your Turnitin report shows *% instead of a number, that is not a glitch and it is not a low score. It is Turnitin refusing to show you a figure it does not trust. In its own words:
“To avoid potential incidence of false positives, no score or highlights are attributed for AI detection scores in the 1% to 19% range. When AI is detected below the 20% threshold in the report, it is now indicated with an asterisk (*%) and no percentage is attributed.”
So the entire band from 1% to 19% is one undifferentiated “not reliable enough to report”. A 3% and a 19% look identical, because the vendor has decided neither number means anything on its own.
Why 20% is not a limit
20% is where Turnitin starts displaying a number. It is not where misconduct begins, and reading it as a cap gets the logic backwards.
The reason the line sits there is accuracy, not severity. Turnitin states a false-positive rate “under 1% for documents with over 20% of AI writing”, validated against more than 700,000 pre-ChatGPT academic papers before each model release. Note the qualifier: that claim is scoped to documents above the threshold. Below it, the company is not claiming that accuracy — which is precisely why it withholds the number.
A department that has adopted “20% or under” as a rule has borrowed a display setting and turned it into a disciplinary one.
What the number actually counts
Not how machine-like your writing sounds. Turnitin defines the percentage as “the amount of qualifying text within the submission that Turnitin’s AI writing detection model determines was likely generated by AI or likely generated and modified by an AI paraphraser or bypasser”.
Two things follow. First, it is a proportion of text, so a long quotation-heavy piece and a short one behave differently. Second, “qualifying text” means prose sentences in long-form writing — lists, bullet points and non-sentence structures are excluded. The denominator is not your whole document, which is why the percentage rarely matches anyone’s intuition about their own work.
GPTZero’s number is a different kind of number
This trips people up constantly, because both are shown as percentages and they are not comparable.
GPTZero returns a document classification — HUMAN_ONLY, MIXED or AI_ONLY — with a probability it describes as “the chance that the detector is correct in its classification”. That is confidence about the tool’s own verdict, not a share of your document. An 85% from GPTZero and an 85% from Turnitin are two unrelated measurements that happen to share a symbol.
GPTZero also publishes its own accuracy at high confidence: “99.1% of human articles are classified as human, and 98.4% of AI articles are classified as AI”. As with any vendor figure, that is measured on data the vendor chose — see what independent testing found, which is consistently less flattering than what vendors report.
Both vendors tell you not to use it alone
This is the part worth quoting back to whoever sent you the score, because it is not our opinion.
Turnitin: the percentage “should not be used as the sole basis for action or a definitive grading measure by instructors”, and the tool “provides data for the educators to make an informed decision based on their academic and institutional policies”.
GPTZero: “These results should not be used to punish students”, and “the sentence-level classification should not be solely used to indicate that an essay contains AI.”
A process resting on the number alone is not following the vendors’ guidance. It is going further than the companies that sell the software are willing to go.
If a score has been used against you
Three specific things to establish, in order: which tool produced it, what that tool’s number actually measures, and what evidence exists beyond it. An asterisk is not a score. A 20% is not a limit. A GPTZero probability is not a proportion.
Then the general guidance applies — what to do when you have been accused and how to prove you wrote it, where draft history does far more work than arguing about a percentage ever will.
Where we stand
We sell a detector, so we have an interest in you believing detection scores mean something. Everything above is quoted from the vendors’ own documentation and linked, and the honest summary is that a score is a weak signal with no defensible cutoff. We have published no accuracy figure for our own detector and will not before our benchmark produces one.