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.

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