Detect GPT estimates whether text was generated by AI using statistical and stylistic signals. Paste content or scan documents to receive likelihood scores and highlighted regions. Use cases include education, editing, and platform policy checks. Extensions and APIs bring detection into everyday workflows. Calibrated thresholds and guidance help reviewers avoid overreliance on any single score.
Analyze burstiness, choice patterns, and structure to estimate AI-likeness. Scores include uncertainty bands, and sampling effects are considered for shorter texts. Explanations clarify what influenced the outcome. Calibration guidance explains limits on very short or heavily edited samples, helping reviewers avoid overconfidence when evidence is ambiguous or mixed in context.
Highlighted passages indicate likely machine-written segments, and comparisons show differences after edits. CSV and PDF exports document findings, and teams can attach notes for follow-up. Exports can include anonymized snippets where policy allows, creating a record that supports training, appeals, or process audits when institutional stakeholders ask for clear documentation.
Browser extensions scan pages or selections, and the API supports batch screening and gates. Role permissions limit access to detailed results, and events record who ran checks and actions taken. Queue endpoints let institutions screen submissions at scale while respecting retention choices and jurisdictional constraints mandated by internal governance policies and agreements.
Set thresholds per context—education, editorial, or platform—and require second reviewers above certain bands. Exclude quotations and citations from scoring, and standardize communications to stakeholders. Contextual templates recommend next steps like requesting drafts or sources, aligning actions with educational or editorial goals so outcomes remain fair, consistent, and transparent.
Retention options define how long text is stored, with sensitive submissions excluded from training. Audit logs support compliance, and regional processing may be available for governance needs. Data controls ensure sensitive material is either never stored or removed on schedule, meeting expectations consistently and building trust with contributors, reviewers, and institutions.
Recommended for educators, editors, and platform teams seeking structured, transparent detection. Detect GPT provides signals and context rather than a black-box label. Policies help keep use fair. APIs and extensions deliver coverage without adding complex new tools to the stack, and clear guidance keeps focus on integrity and learning instead of purely punitive responses.
Unstructured checks are inconsistent and hard to defend. Detect GPT consolidates scoring, highlights, and policy into one process. Integrations meet reviewers where they work. The result is quicker, more consistent decisions with documented rationale. Stakeholders understand outcomes and can appeal with relevant evidence when warranted by the surrounding circumstances.
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