47.69% of 130 injection-manipulated alpha trends have near-linear fits (R2 >= 0.95); 96.15% have roughly linear fits (R2 >= 0.75)

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

• Only 13.27% of 520 non-manipulated alpha trends achieve R2 >= 0.95, contrasting with 47.69% for manipulated trendsfinding0.855
  Control comparison showing near-linearity is specific to the targeted manipulation direction
• 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.finding0.763
  Table 2, row 3, showing equivalence when prior preferences match rewards.
• OLS Linear Regression Fit to Alpha Trendsmethod0.762
  OLS regression fitted to mu(alpha) trends to assess near-linearity of steering with alpha coefficient
• Mass-mean probe directions outperform LR and CCS in causal intervention experiments (NIE) in 7/8 experimental conditionsfinding0.756
  Core result showing MM is superior to LR for causal implication despite similar classification accuracy
• Strength comparison accuracy reaches 73% at layer 3 for injection pair (2,6) vs. 50% chancefinding0.756
  Secondary positive result for strength comparison showing graded sensitivity to perturbation magnitude
• Random direction controls show weak non-significant coupling (ρ=-0.11 to 0.17; R²=0.03–0.11) compared to true probes (∆ρ=0.23–0.79, all p<0.05)finding0.755
  Controls for probe artifacts; demonstrates self-reports carry information specifically about probe-defined concept directions
• Normal (α=0.9) and chronic (α=0.1) agents in Objective-only non-stationary category perform best with opposite learning ratesfinding0.751
  Suggests fundamental differences in learning dynamics between normal and chronic perception models
• Binary detection accuracy (up to 97.3% at L0 α=5) is entirely explained by global logit shifts (r=0.999 correlation with control)finding0.750
  Core negative result: the binary detection paradigm cannot distinguish genuine introspection from uniform output bias