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Governing False Accusations and Abstention in AI Text Detection

Year: 2026

Type: article

Abstract: The project fits the ethics of teaching, assessment, and academic governance. It adds reproducible evidence about how often AI-text detectors wrongly accuse human writers, who bears that risk, and which procedural safeguards should be required before detector output is used in any misconduct decision.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.24093343

Authors: Gatla, Anshu Kumar, Tirumala, Abhinav Reddy

Language: English

Topic: Academic integrity and plagiarism

Subfield: Education

Field: Social Sciences

Domain: Social Sciences

Open Access status: green

OpenAlex ID: W7225615660

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