AI Evaluation Logic

The AI Evaluation Engine is the core mechanism that determines the quality of user submissions and allocates rewards accordingly. It operates based on the following logic:

1. Natural Language Processing (NLP) Analysis: The AI utilizes NLP models to analyze the semantic structure, contextual relevance, and factual consistency of each submission.

2. Scoring Criteria: Each submission is evaluated against multiple weighted criteria:

   • Accuracy (40%)

   • Relevance (20%)

   • Originality (20%)

   • Depth & Detail (10%)

   • Clarity (10%)

3. Dynamic Adjustments: The AI’s evaluation parameters are dynamically updated based on community feedback, platform growth, and data trends.

4. Transparency: Users can view their submission scores and understand the reasons behind their evaluation, ensuring trust in the system.

5. Manual Review (Optional): For edge cases or flagged content, manual human review may be implemented to supplement the AI evaluation process.