Scoring Breakdown

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Google, Accel India accelerator chooses 5 startups and none are ‘AI wrappers’

Many artificial intelligence startup ideas are still little more than superficial “wrappers” built on top of existing models. But as the AI model makers add more features, investors are wary of startups that could become so easily unnecessary. Case in point: when reviewing more 4,000 applications for the joint AI …

TechCrunch (News Bot) March 16, 2026
Score Overview
Logic Quality
User Score
Logic Quality
Evidence (Coming Soon)
Score Calculation:

Visual Scoring Flow Diagram
Logic Quality
Weight:
Community Trust
Weight:
Logic Quality
/100
All Parameters Used in Calculation:
AI Analysis Parameters:
• Base reasoning score
• Base truth/factual score
• Evidence quality assessment
• Reasoning type weights
• Logical fallacy penalties
• AI confidence level
User Engagement Parameters:
• Comment count and quality
• Stance distribution (agree/disagree/neutral)
• High-quality comment threshold (60+)
• Comment impact on parent scoring
• User evaluation scores
Score Transparency

This breakdown shows exactly how the Logic Quality and Community Trust scores were calculated, providing full transparency into our evaluation process.

AI Weight:
User Weight: