Sentence-LevelAI Detection

Sentence-level AI detection estimates AI-likeness for each sentence rather than returning only one score for an entire document. It helps reviewers see which passages contributed more strongly to the result.

It is designed to show variation within a document, including passages that produce stronger or weaker AI-like signals. Those highlights can guide review, but they cannot prove who wrote an individual sentence.

Review the sentence, the surrounding passage, cited sources and available drafts before drawing a conclusion. An isolated flag may reflect formulaic language or limited context, so it should not be treated as a document-wide verdict.

Very short sentences contain less linguistic information and can be harder to classify on their own. Proofademic's published sentence-level methodology uses surrounding context, but every result remains a probabilistic estimate.

A document score summarizes the overall pattern. Sentence-level results add location and granularity, making it easier to inspect mixed or uneven writing without treating every passage the same.

It gives educators and students specific passages to discuss and compare with sources, drafts and writing history. The result remains probabilistic and should not determine misconduct on its own.

No. False positives and false negatives remain possible. Granular results can make an isolated signal easier to identify and contextualize, but they do not eliminate detection error.

Yes. Proofademic supports a print-ready PDF report and a share link so another reviewer can view the results.

It is the F1 score reported in Proofademic’s scoped May 2026 evaluation. The study page describes the dataset, model coverage, protocol and limitations needed to interpret that figure.