Paper Plagiarism Detection & Early Warning System
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About this skill
Problem
In academic workflows, plagiarism findings are often scattered across papers, sources, alerts, and reports. When engineers receive only a similarity score, it is hard to identify high-risk paragraphs, evaluate AI-generated-content claims, or hand off a reviewable workflow. This skill packages those views into one React SPA for demos, integration testing, and customization.
How It Works
The skill provides a React 19 + TypeScript + Vite single-page application. Data is read mainly from src/data/mock.ts, so it runs without a backend. Core modules include: monitoring dashboard with paper counts, average similarity, high-risk totals, and 7-day trends; upload & detection using a simulated Upload → Parse → Detect → Analyze pipeline; detection details split into similar segments, matched sources, and AI conclusions; alert center with critical, warning, and info levels; report manager for weekly, detailed, and alert reports; and an API console with 8 mock REST endpoints. The full-text viewer overlays red, orange, and yellow highlights using character offsets, showing similarity percentages and source titles.
Boundaries
The system uses mock data and client-side generation, making it suitable for prototypes, teaching demos, or front-end scaffolding. Replace generate-detection.ts, upload handling, and the mock APIs before connecting real plagiarism engines, literature services, or file parsing.
Use Cases
- Build a demo dashboard for a paper-integrity product before stakeholder review.
- Use the mock API console to validate upload, detection, alert, and report payload shapes.
- Show learners how highlighted segments, matched sources, and AI conclusions map to paper text.
- Customize mock data, thresholds, and alert levels before wiring a real backend.
Best For
- Front-end engineers who need a backend-free plagiarism workbench prototype.
- Academic platform PMs who need demo-ready dashboard, alert, and report flows.
- AI application developers who need to inspect detection schemas and mock REST contracts.
- Training instructors who need to demo similarity highlights, source matches, and report generation.
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