MARIANA
| Title | Publication Date | Authors | Institutions | Funders | Author Risk |
|---|
🔐 Risk Score Calculation Guide
Overview
The Author Risk Score is a numerical indicator that helps identify potential research security concerns based on affiliations with entities of interest. The score is calculated by matching author and institution names against a curated list of keywords associated with foreign military, defense, and sanctioned organizations.
How It's Calculated
📊 Scoring Method
Each occurrence of a risk keyword found in an author's affiliations adds +1 to the total score. The system scans:
- Raw affiliation strings from the publication
- Institution display names
- All author affiliation data associated with the work
Risk Categories
🎖️ Military & Defense Organizations
Affiliations with military research institutions, defense academies, and armed forces organizations.
🏭 Defense Industrial Base
Companies and corporations involved in military equipment, aerospace, nuclear, and critical technology development.
🎓 Section 1286 Institutions
Universities and research centers identified under Section 1286 of the NDAA with connections to military modernization.
🔬 Section 1260H Entities
Entities identified as Chinese Military Companies under Section 1260H of the NDAA.
⚛️ Nuclear & Advanced Research
Organizations involved in nuclear physics, high-energy research, and dual-use technologies.
Interpreting the Score
| Score Range | Risk Level | Interpretation |
|---|---|---|
| 0 | None | No known risk indicators detected |
| 1-2 | Low | Minor indicators present; may warrant review |
| 3-5 | Medium | Multiple indicators; closer examination recommended |
| 6+ | High | Significant indicators; due diligence strongly advised |
Important Notes
- Not a determination of wrongdoing: A high score indicates potential security concerns that warrant further investigation, not evidence of illegal activity.
- Context matters: Some affiliations may be historical, joint programs, or legitimate academic collaborations.
- Click any risk score in the publications table to see the detailed breakdown of which keywords matched.
- Keyword matching: The system uses both exact matching and relaxed matching for longer organization names to catch variants and abbreviations.