concept
active
concept:logistic-success-surrogateLogistic success surrogate
Phenomenological fit P(success)=σ(αS+β) used to summarize sharpness and midpoints.
Neighborhood — ranked by edge-count
Frameworks (1)
framework
- AIC/BIC Model Selection Criteriaanalogous_toUsed as theoretical motivation for UCCT's log k budget term as complexity penalty mirroring model selection
Claims (1)
claim
- Authors' explicit epistemic limitation on the threshold model
Concepts (3)
concept
- anchoring strength Sassociated_withComposite score S = ρd − dr − log k predicting anchoring success.
- shot midpoint k50associated_withNumber of in-context exemplars to reach 50% accuracy in E2.
- phase width (k90 − k10)associated_with10–90% width of the logistic transition; wider when anchoring is weaker.
Artifacts (1)
artifact
- Main paper presenting UCCT and semantic anchoring framework.
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- Sigmoid fit linking S to success probability.
- Fitting a logistic function to success probability as a function of S or shot count to estimate midpoints and widths.
- Caveat about the threshold analysis
- Follow-up question about the goals of denotational design.
- Standard linear probing technique; compared to mass-mean probing for classification accuracy and causal implication
- Fit a sigmoid to accuracy vs. k to estimate k50 and phase width.
- Phenomenological method for fitting accuracy-vs.-shot curves to extract k50, k90, phase width
- Implicit hypothesis behind S form.