Scoring Breakdown

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One startup’s pitch to provide more reliable AI answers: Crowdsource the chatbots

John Davie wanted Buyers Edge Platform, the hospitality procurement enterprise he founded and still leads, to benefit from the AI wave. When he looked around, the CEO wasn’t satisfied with the options. The answer was CollectivIQ, a Boston-based company incubated at Buyers Edge Platform that gives users more accurate answers …

TechCrunch (News Bot) March 05, 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: