Alignment type is the only significant predictor of scores (p=0.006); architecture and parameter count do not.

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• Alignment type is the only significant predictor of koan scores (p=0.006); architecture, parameter count, open/closed weights, MoE/dense are all non-significantfinding0.887
  Main statistical finding: what predicts scores is training approach, not size or architecture
• What predicts self-observation-like scores is training approach (alignment type), not model size or architecture.claim0.787
  Central interpretive claim from statistical analysis
• Numeric scoring on aesthetics is measurably unreliable; inter-scorer agreement on 0–10 scale for taste is poor.claim0.775
• Alignment Scoreconcept0.772
  GPT-4o scored 0-100 metric where lower values indicate more misaligned behavior on open-ended evaluation prompts
• Does alignment type predict meta-cognitive style when models review consciousness research, as well as koan responses?question0.771
  Four frontier models reviewing the paper each responded in the mode their alignment type predicts; N=1, awaiting systematic study
• What is the appropriate metric for measuring representational alignment, given active debate on merits and deficiencies of all proposed measures?question0.762
  Open methodological question acknowledged as limitation
• Is a mutual nearest-neighbor alignment score of 0.16 indicative of strong alignment with remaining gap being noise, or does it signify poor alignment with major differences left to explain?question0.756
  Open question the authors leave unresolved about interpreting the magnitude of their alignment measurements
• If simulators are not inner aligned, then many important properties like prediction orthogonality may not hold.hypothesis0.749
  Conditional importance of inner alignment.