Competition problems and datasets demonstrate connections in geometry and machine learning, suggesting potential insights.
FINDING: Putnam problem with elegant solution; IMO windmill problem; average cube shadow area; MATH dataset for machine learning. | MATH: No specific equations or constants extracted from summaries; average cube shadow area involves integral geometry (likely π/6 or similar). | CONNECTION: No explicit geometric harmony ratios (0.382, 0.618, etc.) or base-60, crystallographic symmetries found in these summaries. | DEPTH: 2 — These are competition problems and dataset descriptions, not fundamental discoveries. No profound mathematical constants or symmetries revealed. Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com
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Andrew Stewart Caldin (2026) studied this question.
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