Phase 0 State-Separability Validation Protocol (CAIS) A Cross-Laboratory Reproducibility Framework for Molecular–Electrochemical Signal Classification

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Authors: JINHO LEE
Cited by: 3

Abstract

This document does not attempt to prove “consciousness.” It fixes a far narrower, experimentally answerable question: Can controlled human state transitions (sleep, meditation, acute stress, selective anesthesia) produce statistically separable patterns in a molecular–electrochemical interface? Phase 0 is not philosophical.It is operational. You do not need a new device.You do not need a large cohort.You do not need to adopt any ontology. You need only: • A time-series electrochemical signal (≥1 Hz recommended)• A structured session: Baseline → Induction → Recovery• Timestamped state labels• A pre-declared feature extraction pipeline• Cross-validated classification• A decision rule (≥65% cross-validated accuracy) If separability emerges, interface sensitivity is demonstrated.If performance remains at chance level, a boundary condition is established. Both outcomes are scientifically valuable. The protocol is deliberately protective of participating investigators: • Mandatory negative controls (artifact detection safeguard)• Explicit leakage firewall rules• Session-separated folds• No post-hoc hyperparameter tuning• Drift stabilization requirements• Optional permutation testing for robustness• Hash-lockable, replayable dataset structure (Engineering Compliance Annex) This framework does not demand belief.It demands measurement discipline. Phase 0 tests structure only.It does not claim interpretation.It does not assert ontology.It does not claim clinical meaning. It asks one falsifiable question:Is state-dependent signal clustering detectable under reproducible laboratory conditions? This is a minimal-entry, lab-ready protocol. If you have ever wondered whether physiological state transitions leave detectable molecular–electrochemical footprints — and you would prefer to test that boundary directly rather than debate it — Phase 0 is your entry point. Author: Jinho Lee, MD Salpida Institute of Consciousness Science (SICS) Seoul, Republic of Korea License: CC BY-SA 4.0

Fields of Study & Subjects

EEG and Brain-Computer Interfaces Advanced Chemical Sensor Technologies Emotion and Mood Recognition

Publication details

Journal / source
PhilPapers (PhilPapers Foundation)
Publication date
15 February 2026
Language
EN