HealingTrialData
HealingTrialData records measurements from one healing trial as distance, effect size, and PLV change. Experimental physicists testing coherence transfer predictions would cite it when logging data for distance-decay checks. The declaration is a plain record type with three real fields and no computational content or axioms.
claimA healing trial datum is a triple $(d, e, p)$ with $d, e, p : ℝ$, where $d$ is distance, $e$ is effect size, and $p$ is PLV change.
background
The structure sits inside the experimental protocols module, which formalizes testable predictions from voxel theory. Core items include EEG φ-frequency peaks, mode-ratio classification of consciousness states, and healing via coherence transfer through Θ-coupling. All entries are treated as hypotheses equipped with explicit falsification criteria rather than derived theorems.
proof idea
The declaration is a structure definition introducing three fields of type ℝ. No lemmas or tactics are applied; it functions solely as a data container passed to downstream predicates such as isHealingFalsified.
why it matters in Recognition Science
HealingTrialData supplies the input type for isHealingFalsified, which tests whether effect size decays with distance to falsify the coherence-transfer prediction. It implements the healing protocol listed in the module doc-comment and connects to the broader set of empirical checks derived from the phi-ladder and eight-tick octave, though it does not invoke any T0-T8 forcing steps directly.
scope and limits
- Does not compute correlation or apply any statistical threshold.
- Does not specify measurement units or acquisition protocols for the fields.
- Does not include control or baseline trial records.
- Does not impose sign or magnitude constraints on the real values.
formal statement (Lean)
156structure HealingTrialData where
157 distance : ℝ
158 effect_size : ℝ
159 plv_change : ℝ
160
161/-- The healing prediction is falsified if effect decays significantly with distance -/