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Stop AI-Generated Fake Authors at Submission

Conference paper submission filter that detects AI-generated author bios, fabricated affiliations, and synthetic researcher profiles using Claude API - protecting journal integrity and reviewer credibility.

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The Problem

Academic conferences face an unprecedented wave of submissions with fabricated author credentials:

  • Fake or inflated institutional affiliations to appear more credible
  • AI-written author bios that lack genuine research history or expertise
  • Synthetic researcher profiles designed to bypass peer review systems
  • Mass submissions from coordinated networks using identical bio templates

Editorial teams manually flag these submissions, consuming hours per conference. False submissions waste reviewer bandwidth and undermine paper quality.

How It Works

1

Ingest Submission Data

Connect your submission platform (OJS, Scholar One, Easychair) or upload CSV with author names, bios, and affiliations.

2

Analyze with Claude

Send author profiles to Claude API. The model checks: tone consistency with genuine researchers, plausibility of affiliation + bio pairing, patterns indicative of synthetic generation.

3

Get Risk Score & Reasoning

Receive confidence scores (0-100) for each author profile: synthetic-generated, overinflated credentials, institutional mismatch. Detailed reasoning for editorial review.

4

Act on Signals

Flag high-risk submissions for manual review. Admins can reject outright or request author verification. Reduce false positives via editorial override feedback.

Key Features

Synthetic Bio Detection

Identifies author bios written by AI models using linguistic and structural patterns that distinguish generated from human-authored text.

Affiliation Verification

Cross-references institutional claims with public databases. Flags implausible or fabricated university affiliations.

Credential Plausibility

Checks consistency between claimed expertise, publication history (if available), and bio narrative. Catches overinflated or contradictory credentials.

Batch Processing

Process 100+ submissions in minutes. Scale with conference size. No per-author cap or manual bottleneck.

Editorial Dashboard

Web interface for review teams. Sort by risk score, bulk-action flagged submissions, export reports for board review.

Feedback Loop

Editors override false positives to retrain the filter. Improves accuracy over time for your specific conference discipline.

Who Benefits

Conference Organizers: Reduce manual vetting of 500+ submissions by 40-60%. Focus editor time on paper quality, not author credential validation.

Editorial Teams: Get AI-backed risk signals, not binary accept/reject. Make faster, more confident decisions about suspicious submissions.

Reviewers: Receive only submissions with credible author bios. Fewer "fake" papers waste review time and dilute conference reputation.

Pricing

Small Conference (< 200 submissions)
$1,200 per conference cycle. Includes setup, batch processing, and 90 days of dashboard access.
Mid-Tier Conference (200-1000 submissions)
$3,500 per cycle. Add custom training for your discipline, feedback loop tuning, and extended support.
Large/Recurring Conference (1000+ submissions)
$8,000+/year. Dedicated integration with your submission platform, multi-conference access, and priority API rate limits.

Ready to Protect Your Submissions?

Let's talk. Schedule a 15-minute call with our team to discuss your conference's author vetting challenges, see a live demo, and explore a custom plan.

Get Started

Built for academic integrity. Powered by Claude API.

Resources for this product
  • FAQ
  • Email drip
  • Outreach pack
  • Skeptic memos (2)

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