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AuthorVerify: Author Identity & Submission Integrity Service

A human-powered verification service that journals contract to vet author identities and flag high-risk submissions before peer review. Combines identity verification (cross-referencing institutional affiliations, prior publications, ORCID records, email domain validation), writing-pattern analysis by trained reviewers, and submission metadata audits to catch ghostwriting, duplicate submissions, and fake author networks. Results delivered within 48–72 hours with a risk score and detailed report.

SERVICE

28 weeks • 70% confidence

Value Proposition

Eliminates slow, inconsistent manual verification by centralizing it into a repeatable, auditable process. Catches fraud BEFORE peer review (saving reviewer time and journal reputation), costs less than hiring full-time editorial staff, and provides journals with defensible due-diligence records for compliance and liability protection.

Target Audience

Mid-to-large academic journals (100+ submissions/year), journal management systems (ScholarOne, Editorial Manager), and academic publishers seeking to reduce retraction risk and reviewer burden.

Key Features

  • ORCID/institutional affiliation cross-check against public academic databases
  • Writing-style consistency analysis comparing submission to author's prior published work
  • Metadata audit: email domain legitimacy, author name consistency, submission timing patterns
  • And more, with full implementation detail...

Tech Stack

ORCID API and institutional affiliation databases (CrossRef, Scopus API) Email verification tools (Hunter.io, RocketReach) Plagiarism/writing-pattern baseline tools (Turnitin API or open-source alternatives) Simple backend (Node.js/Python) for queue management and risk-scoring logic
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Original Problem

Academic journals struggle to verify author authenticity and detect fraudulent submissions

Journal editors and peer reviewers lack efficient tools to verify that authors are real people and that submissions aren't fabricated or ghostwritten by bad actors. This creates reputational risk, wastes reviewer time on fake papers, and undermines the integrity of academic publishing. Current manual verification processes are slow, inconsistent, and easily bypassed.

Score: 53.7%

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