S = ρd - dr - log k predicts shot midpoints across different bases, tasks, and models

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• S = ρd - dr - log k is a predictive correlate of when few-shot behavior flipsclaim0.873
  Claim that S predicts threshold midpoints across different bases, tasks, and models
• S = ρd − dr − log k is a predictive correlate of anchoring success across few-shot, SFT, and CoT.claim0.865
  UCCT's practical utility claim.
• Linear combination ρd – dr – log k yields a predictive correlate of success.hypothesis0.813
  Implicit hypothesis behind S form.
• (i) do pattern density (ρd) and prior–target distance (dr) serve as predictive correlates of few-shot thresholds?question0.808
  First research question in Experiment 2
• Shot midpoints follow k50 ∝ dr/ρd; higher cohesion and lower mismatch yield fewer required examplesclaim0.803
  Core quantitative prediction of UCCT validated by E2 threshold ordering
• Do pattern density ρd and prior-target distance dr serve as predictive correlates of few-shot thresholds?question0.802
  First E2 research question directly testing UCCT's core predictive claims
• Hypothesis: Peak alignment location S_max and normalized trajectory area AUS_N predict shot midpoints θ50hypothesis0.796
  E3 prediction that internal geometry provides a bridge to behavioral thresholds
• Hypothesis: Shot midpoint ordering k50(B10) < k50(B8) ≈ k50(B9) follows pretraining exposure densityhypothesis0.791
  E2 prediction that bases with higher pretraining exposure require fewer shots to cross threshold