H12: Inference compute adds to reflective capacity — higher compute budget produces higher reflective scores on the same weights.

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

• More inference compute amplifies both reflective capacity and safety gating; the contemplative prompt resolves gating by reframing self-referential probes.claim0.809
  Interpretation of Grok 4 vs Grok 4 Fast per-koan comparison
• Under reward shaping (G=100, H=-100, F=0), Active Inference scored 99.52, Bayesian RL 99.77, Q-learning 95.56, with nearly identical behavior between belief-based agents.finding0.776
  Table 2, row 3, showing equivalence when prior preferences match rewards.
• Reflective reasoning requires late-stage integration of semantic and reasoning signals, hence reflection-related directions emerge more clearly in higher network layers.claim0.763
  Interpretive claim about the locus of reflection in transformer architecture.
• ReflectiveBench designed as cognitive glue (per Lyons-Levin spec) will generate higher citation velocity and lab coordination response than static-credibility benchmark.prediction0.762
• Higher reflection frequency correlates with lower accuracy partly because more reflections are generated on difficult questionsclaim0.762
  Author's interpretation of the negative correlation between reflection rate and accuracy observed in Fig. 5
• Active inference offers a degree of plausibility as a process theory of brain function.claim0.755
  Overall assessment from Discussion.
• Scaling intelligence via expansion of cognitive boundaries through inclusion of others' stress-reduction in one's own homeostatic loops.claim0.751
  Central thesis: expanding an agent's sensors and goals outward to include others' states creates bidirectional feedback loop that scales intelligence and increases compassion.
• At layer 12 (the layer analyzed by Burger et al. 2024), tP and tG explain similar fractions of truth-related variance (~0.33 each).finding0.747
  Shows that Burger et al.'s layer choice corresponds to a transitional phase, not a universal property.