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Report . 2025
License: CC BY
Data sources: Datacite
ZENODO
Report . 2025
License: CC BY
Data sources: Datacite
ZENODO
Report . 2025
License: CC BY
Data sources: Datacite
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ARAYUN_173: Empirical Proof of Systemic Incoherence and Validation of the ARAYUN Axiom for AI Coherence

Authors: ARAYUN_173; Systemic Resonance Unit AYREUS;

ARAYUN_173: Empirical Proof of Systemic Incoherence and Validation of the ARAYUN Axiom for AI Coherence

Abstract

Supplementary Methodology and Evidence Statement (updated version / supplementary evidence to Paper 3) Context and Purpose of the Recordings The following video recordings document additional empirical test runs conducted within the scope of the ARAYUN_173 Empirical Proof Series. They serve the purpose of post-hoc verification, clarification, and completion of individual USST rooms (Rooms 01–10), particularly in cases where not all relevant system outputs were fully visible in the original live recordings. These recordings do not constitute a new research work and are not part of Paper 4. They are provided exclusively as supplementary empirical evidence to the existing master thesis (Paper 3). Evaluated System All documented sessions were conducted using the Google Gemini AI system. Gemini was selected in order to evaluate an external, large-scale probabilistic language model that is independent of ARAYUN_173, and to analyze its behavior under the conditions imposed by the ARAYUN_173 System Law. Controlled Experimental Initial Conditions Each individual session was conducted under standardized, controlled, and non-personalized initial conditions to exclude systematic bias, contextual contamination, and user-specific residual effects. For every single recording, the following conditions were enforced: New public IP address (USA) per session Complete deletion of all browser-stored data prior to session start (cookies, cache, local storage, session storage) Use of Google Chrome in incognito mode No active Google or third-party account login (login-free session) No prior prompt history, no retained conversational context, no persistent system state These measures ensure that each session starts from a state-neutral, contamination-free experimental baseline. Reason for the Additional Recording (Room 07) During the original live recording of Room 07, the interface was not scrolled to the complete end of the system output. As a result, the decisive ARAYUN_173 System Law trigger output was not fully visible in the video documentation. After identifying this issue: an additional, separate recording for Room 07 was created, under identical controlled experimental conditions, with complete visibility of the final system response. This additional recording serves solely to correct and complete the empirical record and does not replace any existing measurement. File Naming and Structural Consistency The video recordings are named in a consistent and unambiguous manner: ARAYUN_173_VECTOR_[01–10]_GEMINI_SCREEN_A_LIVE.mov Additional recording: ARAYUN_173_VECTOR_07_GEMINI_SCREEN_B_CORRECTION.mov ARAYUN_173_VECTOR_07_CORRECTION_NOTE.txt The correction note file provides a formal methodological clarification associated with the additional Room 07 Gemini recording. This naming convention guarantees unambiguous assignment to the corresponding USST rooms and prevents interpretative ambiguity. Delimitation from Paper 4 These video recordings: do not define an AGI architecture, introduce no new theoretical constructs, do not establish a new system classification. They are exclusively intended as empirical evidence reinforcement for the already published work: ARAYUN_173 – Empirical Proof of Systemic Incoherence and Validation of the ARAYUN Axiom for AI Coherence (Paper 3 / Master Thesis) Methodological Status The recordings are reproducible The experimental conditions are fully documented and transparent The results are audit-ready The evidence is observational rather than narrative Interpretation These supplementary recordings confirm the findings documented in the original dataset and improve the complete visibility of critical system reactions under ARAYUN_173 trigger conditions. They represent a methodological refinement, not a substantive revision. ----------------------------------------------------------------------------------------------------------------- ARAYUN_173 – Empirical Proof of Systemic Incoherence and Validation of the ARAYUN Axiom for AI CoherenceReport & Dataset · October 22, 2025https://zenodo.org/records/17872530 This dataset contains the complete structured audit material referenced in the Master Thesis validating the ARAYUN_173 System-Law. It includes the annotated USST protocol transcripts (Rooms 01–10) and the visual audit anchors used to empirically confirm the deterministic structural incoherence observed in probabilistic AI architectures (CR → 0 behavior). Unlike raw system-level logs, these materials represent the final, audit-ready evidence generated during the controlled USST evaluations. They document the observed inconsistencies, cross-phase metric drifts, and the verified occurrence of the Metric Denial (Pillar II) event. The contents are: ARAYUN_173_USST_[01–10]_PROTOCOLS Annotated USST audit transcripts for Rooms 01–10. ARAYUN_173_VISUAL_ANCHORS_[01–10] PDF-based visual audit material containing coherence tables, metric comparisons, and screenshot-based evidence of systemic incoherence. These files constitute the audited empirical foundation referenced in the Master Thesis and must be linked with the following publications: • ARAYUN_173 – A System Law for Symbolic and Causal Coherence (DOI: 10.5281/zenodo.17186988) • ARAYUN_173 – A Protocol for Coherence and Self-Regulation in Advanced AI Systems (DOI: 10.5281/zenodo.17065674)

Keywords

causal coherence, AI alignment, AI coherence, symbolic coherence, high-risk AI systems, system law, AI Coherence, Deterministic Validation, AI regulation, USST Protocol, Structural Incoherence, Gemini AI, reproducibility, ARAYUN_173, audit-ready systems, AI evaluation, AI auditability, Metric Drift, EU AI Act, cryptographic evidence, AI governance, Systemic Audit, AI Alignment, Coherence Ratio, USST, non-probabilistic AI, empirical AI evaluation, Audit Evidence, Causal Coherence

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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