(ii) does the anchoring score S = ρd − dr − log k consistently correlate with performance across anchoring methods?

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

• S = ρd − dr − log k is a predictive correlate of anchoring success across few-shot, SFT, and CoT.claim0.862
  UCCT's practical utility claim.
• Anchoring strength S = ρd - dr - log kconcept0.844
  The calibrated score measuring how effectively anchors bind target patterns; a predictive correlate of success.
• The anchoring score S is a predictive correlate of when anchoring succeeds and why small prompt changes yield threshold-like shifts.claim0.832
  A central claim about the operational value of S.
• layer-wise anchoring score S(ℓ) computationmethod0.787
  Compute per-layer S(ℓ) = ρ̃d(ℓ) - d̃r(ℓ) - log k after whitening and standardization.
• S = ρd - dr - log k predicts shot midpoints across different bases, tasks, and modelsclaim0.786
  Predictive practical utility claim.
• S = ρd - dr - log k is a predictive correlate of when few-shot behavior flipsclaim0.784
  Claim that S predicts threshold midpoints across different bases, tasks, and models
• Linear combination ρd – dr – log k yields a predictive correlate of success.hypothesis0.775
  Implicit hypothesis behind S form.
• The additive form S = ρd - dr - log k is parsimonious and aligns with log-odds intuitionclaim0.757
  Justification for the linear combination