Red Flag Identification Cards

These printable reference cards are designed to help researchers, reviewers, and editors quickly identify potential signs of AI-generated scientific content. Each card focuses on a different aspect of scientific writing where AI-generated content often shows distinctive patterns.

How to Use These Cards

Print these cards on standard cardstock, cut along the outlines, and keep them handy during paper reviews or when evaluating scientific content. The cards are organized by categories of red flags to watch for.

To print the cards:

  1. Click the "Print Cards" button below
  2. In your browser's print dialog, select "Scale: 100%" (not "Fit to page")
  3. For best results, print on cardstock or other sturdy paper
  4. Cut along the card outlines
Data & Results Red Flags
  • Unrealistically precise values without error ranges
  • Perfect or near-perfect correlations (r² > 0.99)
  • Data that perfectly matches theoretical predictions
  • Complete absence of outliers or anomalies
  • Uniform error bars across varying conditions
Example: "The measured coherence time was 142.57 ns at room temperature, precisely matching our theoretical prediction."
Methods Red Flags
  • Vague equipment descriptions without specific models
  • No mention of calibration procedures
  • Absence of method optimization or failures
  • Perfect protocol performance without troubleshooting
  • Missing crucial experimental parameters
Example: "Samples were analyzed using standard spectroscopic techniques following established protocols."
Language Red Flags
  • Absolutist terms: "perfect," "complete," "all"
  • Revolutionary claims: "paradigm-shifting," "solves all issues"
  • Excessive use of superlatives: "unprecedented," "extraordinary"
  • Perfect formatting with no stylistic variations
  • Consistently uniform paragraph structures
Example: "Our breakthrough completely eliminates all limitations of previous approaches, revolutionizing the entire field."
Mathematical Models Red Flags
  • Equations without physical justification
  • Perfect mathematical relationships in complex systems
  • Arbitrary exponents or constants (e.g., T⁰·⁶⁷)
  • Models that ignore known physical constraints
  • Equations that conveniently produce desired results
Example: "We discovered that quantum coherence follows τ = τ₀(1+N/N₀)³/² where N is qubit number."
Citations Red Flags
  • References that don't support specific claims
  • Citations to papers that don't exist
  • Reference to methods without specific citation
  • Citing reviews rather than primary literature
  • Uniform distribution of citations throughout text
Example: "Quantum dots exhibit room-temperature coherence [12-15]" where references 12-15 don't discuss this phenomenon.
Limitations Red Flags
  • No discussion of study limitations
  • Dismissal of fundamental physical constraints
  • No acknowledgment of experimental uncertainties
  • Claims that all challenges have been solved
  • Perfect results without caveats or conditions
Example: "Our approach works perfectly across all conditions and completely eliminates the need for further optimization."
Figure/Image Red Flags
  • Suspiciously clean data without experimental noise
  • Perfect symmetry in experimental results
  • Images that look computer-generated rather than measured
  • Identical patterns in supposedly different samples
  • Missing scale bars or crucial experimental details
Example: Perfect linear relationships in biological systems where variability would normally be expected.
Terminology Red Flags
  • Novel terms that sound scientific but aren't established
  • Misuse of domain-specific technical terminology
  • Jargon that doesn't actually exist in the field
  • Quantum-prefixed terms outside quantum physics
  • Terms that combine unrelated scientific concepts
Example: "We leveraged Quantum Neural Biophysical Integration (QNBI) to optimize gene expression."
Implementation Red Flags
  • No discussion of practical implementation challenges
  • Unrealistic timelines for application ("within months")
  • Ignoring regulatory or ethical considerations
  • Claims of immediate clinical application
  • Overlooking real-world constraints (cost, scalability)
Example: "This technology will be immediately implemented in all hospitals worldwide, completely eliminating the disease."
Verification Questions to Ask
  • What were the biggest technical challenges faced?
  • How many failed attempts preceded the successful one?
  • What specific equipment models and settings were used?
  • Can you provide the raw data files for verification?
  • How would this perform under [specific adverse condition]?
AI-generated content typically struggles to provide specific answers to these questions.