The logistic fit for threshold behavior is a phenomenological surrogate for interpretability, not a mechanistic derivation

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• The logistic surrogate is a phenomenological fit, not a mechanistic derivationclaim0.883
  Caveat about the threshold analysis
• logistic fitting for shot thresholdsmethod0.822
  Fit a sigmoid to accuracy vs. k to estimate k50 and phase width.
• Hypothesis 1 (Threshold Behavior): There exists a task-dependent threshold Sc such that performance exhibits sharp changes as S crosses Sc, with value and transition width depending on model, layer, and poolinghypothesis0.796
  Core testable hypothesis of UCCT about the nature of performance transitions under anchoring
• A generalized model where Level 2 modulates all Level 1 precision parameters would capture mood, emotion, and broader phenomenology of mental states.hypothesis0.771
  Future work direction; extends current model beyond attentional precision to full space of emotional and metacognitive phenomena.
• Logistic surrogate fittingmethod0.771
  Fitting a logistic function to success probability as a function of S or shot count to estimate midpoints and widths.
• acting to optimize value and perception are two aspects of exactly the same principle; namely the minimisation of a quantity [free energy] that bounds the probability of sensory input, given a particular agent or phenotype.quote0.769
  Concise statement of the free-energy principle's unification of action and perception.
• Any system that persists must minimise surprisal, thereby gathering evidence for its own generative model, a process known as self-evidencing.claim0.764
  Foundational claim of the paper, defining self-evidencing.
• The systematic behavioral shift of LLMs under self-referential processing conditions predicted by consciousness theories represents something more structured than superficial correlations in training dataclaim0.764
  The paper's claim that theoretical convergence across GWT, RPT, HOT, IIT makes the findings non-coincidental