Table 1: Unhealthy present-day percentages (Berkeley): Yellow 2%, Green 28%, Gray 23%, Red 47%

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

• Table 2: Healthy percentages target: Yellow 25%, Green 25%, Gray 25%, Red 25%finding0.825
  Ideal balance of the four colors for a living neighborhood derived from the model.
• Diagnostic mapping of yellow, green, gray, red percentagesmethod0.714
  A technique to evaluate neighborhood health by measuring the area percentages of pedestrian, garden, building, and car space.
• Strong dark blue more harmonious than weak blue with red and yellowfinding0.703
  In color tests, a strong dark blue version created better harmony with the middle red and pale yellow than a weak blue.
• Generated statements achieve 85.62%-94.00% cosine similarity alignment with Perez et al. validated OCEAN and Dark Triad statementsfinding0.697
  Validates the statement synthesis pipeline as producing behavior-specific content comparable to established methods
• SFR-DR-20B achieves 28.7% on Humanity's Last Exam full text-only benchmark, 65% relative improvement over gpt-oss-20b baseline.finding0.691
  Main evaluation result showing best variant outperforms many proprietary and open-source baselines of comparable or larger sizes.
• Color proportion 57% middle red, 40% very pale yellow, 3% strong blue yielded freshness and spring-like quality for Martinez floorfinding0.690
  After sliding paper swatches, the exact proportions that made the balance just right were discovered; any deviation destroyed the inner light.
• G2.5-FL overbid rate=1.20%, highest among all agentsfinding0.689
  highest overbid frequency observed
• Normal (α=0.9) and chronic (α=0.1) agents in Objective-only non-stationary category perform best with opposite learning ratesfinding0.688
  Suggests fundamental differences in learning dynamics between normal and chronic perception models