StealthWriter vs Turnitin: What the Documentation Actually Says

StealthWriter's FAQ defines its detector score as the percentage of input it classifies as natural. Turnitin describes an AI Writing percentage generated by the process documented below. The checked sources provide no conversion rule between those two labels, so a number from one product cannot be translated into a number from the other.

There is no universal AI-detection score that all tools converge on, and why the same text scores differently on every detector traces where the gap comes from. Each detector produces its own estimate. Treating scores from different tools as if they measure the same thing in the same units leads to confusion.

We are not making a claim about which tool is more accurate. No cross-vendor accuracy or agreement test was reproduced for this article. Each result has to be read against its vendor's own definition.

Turnitin documents a specific process for arriving at its AI writing score:

"When a paper is submitted to Turnitin, sentences from the submission are extracted and segmented into overlapping sections for prediction analysis. Each segment is classified by the AI detection model and given a value between 0 and 1, denoting the probability of the text being likely human or AI-generated. Each qualifying sentence within these segments inherits the segment's score. Since segments overlap, some sentences may have multiple scores, which are then pooled into a single score. These sentence scores are further aggregated and used to compute the overall document AI writing score."

The process involves extracting sentences, segmenting them into overlapping units, scoring each segment, pooling sentence scores, and aggregating them into a document-level percentage. The StealthWriter public pages checked for this article do not document an equivalent segmentation and aggregation pipeline. Current sources therefore do not support saying that StealthWriter uses either the same method or a different one.

Turnitin's documentation also clarifies that the AI writing detection percentage and the Similarity score are separate. "The Similarity score and the AI writing detection percentage are completely independent and do not influence each other." The Similarity score indicates the percentage of matching text found in the submitted document when compared to Turnitin's comprehensive collection of content for similarity checking. A document can have high similarity and low AI, or vice versa. Turnitin AI writing report vs Similarity report keeps the two apart. The two numbers do not influence each other.

Turnitin publishes a specific false positive target:

"We strive to maximize the effectiveness of our detector while keeping our false positive rate - incorrectly identifying fully human-written text as AI-generated - under 1% for documents with over 20% of AI writing."

The documentation restates this as: "In other words, we might flag a human-written document as AI-written for one out of every 100 fully-human written documents." This restatement drops the "over 20% AI writing" qualifier. The version with the 20% threshold is more precise. What that threshold does and does not imply about your own score is covered in is 20% AI too high.

To validate this target, Turnitin describes its testing framework: "To bolster our testing framework and diagnose statistical trends of false positives, before every update or new model release, we perform tests on over 700,000 additional academic papers that were written before the release of ChatGPT to further validate our less than 1% false positive rate."

This is what Turnitin says about its own system. StealthWriter may have different accuracy targets, different validation processes, or may not publish comparable figures. We cannot make a direct accuracy comparison. We can only report what Turnitin's documentation states.

Document length affects how Turnitin's detector processes text. For short documents, the scoring mechanism behaves differently. The documentation states:

"In shorter documents where there are only a few hundred words, the prediction will be mostly 'all or nothing' because we're predicting on a single segment without the opportunity to overlap."

"This means that some text that is a mix of AI-generated and original content could be flagged as entirely AI-generated."

The overlap mechanism that averages out scores in longer documents does not operate when the text is a single segment. A few hundred words of mixed human and AI content could return a 100% score, one of the paths into why Turnitin says your work is 100% AI. This is a structural behavior on short inputs.

This short-input behavior is documented for Turnitin. The checked StealthWriter pages do not describe an equivalent short-input process, so this article does not attribute a matching or different mechanism to StealthWriter.

Turnitin suppresses numeric scores below 20%. The documentation states:

"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."

A document that Turnitin's model estimates at 8% AI will show an asterisk in the report, not the number 8%. No highlights are applied to the text. The rationale is to avoid surfacing potential false positives in a low-confidence range, which what the asterisk (*%) means on a Turnitin AI score goes into.

The asterisk rule belongs to Turnitin. The checked StealthWriter pages define their own score but do not document how the same low-value case would be displayed. Do not infer a conversion or display difference without a separate, documented test.

If you are comparing StealthWriter and Turnitin results on the same document, here is the summary:

• Different definitions, no conversion rule. StealthWriter defines a naturalness percentage, while Turnitin documents an AI Writing score. The checked sources provide no mapping between them.
• Turnitin scores by segmenting and aggregating. Sentences are extracted, segmented into overlapping units, scored, pooled, and aggregated. The AI score and Similarity score are fully independent.
• Turnitin targets under 1% false positives for documents with over 20% AI writing, validated against over 700,000 additional academic papers written before ChatGPT.
• Short documents get all-or-nothing scores. A few hundred words may come back as 0% or 100% even for mixed text.
• Scores below 20% show as an asterisk. No numeric percentage or highlights appear in the 1-19% range.

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