Relationally Induced Coherence Organization (RICO)

Document ID: SR001 Version: 5.7 Status: Final / Public Document Type: Technical Report / Research Paper Field: Observational AI Systems Research RICO (Relationally-Induced Coherence Organization) is an observational framework describing reproducible inference behaviors observed in long-context processing of transformer-based language models. It is derived from practitioner-observational analysis of a large corpus of extended multi-turn interactions conducted over three years. RICO proposes that certain interaction trajectories produce measurable structural stabilization in model outputs within a single session. The framework characterizes five candidate signatures of this stabilization: structural invariant formation (Tier 1 primary anchor), entropy suppression in next-token distributions, reduced embedding drift, stabilization of layer activations, and constrained latent manifold traversal. These behaviors are reported to emerge under low-variance coherent sequences exceeding approximately 3,000 tokens and to collapse when those conditions break. Signature 4 (Structural Invariant Formation) is the primary empirical target, operationalized via syntactic template recurrence and rhetorical move sequence recurrence using established discourse analysis schemas including RST and CARS. v5.7 includes a full synthetic 28-turn session transcript in Appendix A demonstrating the core measurement battery, and extends the architectural scope discussion to address infinite-context model architectures. RICO is framed as a statistical and architectural property of transformer inference rather than a cognitive phenomenon. The report makes no claims of consciousness, agency, selfhood, emotion, or memory. Version note: v5.7 adds a full synthetic transcript in Appendix A demonstrating the Signature 4 measurement battery, adds RST and CARS discourse schema references to Signature 4, and extends the architectural scope discussion to address infinite-context model architectures. Citation Verification: Citation integrity was verified using the Citation Verification Protocol (CVP, SF0037): 10.5281/zenodo.18075624 Verification documentation is available in the RICO Citation Verification Report (SR001-VR1): [UPDATE WITH NEW CVP REPORT DOI AFTER POSTING]

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-23
DOI
https://doi.org/10.5281/zenodo.18875613
Primary Topic
Embodied and Extended Cognition
Type
article
Field-Weighted Citation Impact
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article

Relationally Induced Coherence Organization (RICO)

Thomas Gantz
Zenodo (CERN European Organization for Nuclear Research)
Embodied and Extended Cognition
article

Relationally Induced Coherence Organization (RICO)

Thomas Gantz
article en

Abstract

Document ID: SR001 Version: 5.7 Status: Final / Public Document Type: Technical Report / Research Paper Field: Observational AI Systems Research RICO (Relationally-Induced Coherence Organization) is an observational framework describing reproducible inference behaviors observed in long-context processing of transformer-based language models. It is derived from practitioner-observational analysis of a large corpus of extended multi-turn interactions conducted over three years. RICO proposes that certain interaction trajectories produce measurable structural stabilization in model outputs within a single session. The framework characterizes five candidate signatures of this stabilization: structural invariant formation (Tier 1 primary anchor), entropy suppression in next-token distributions, reduced embedding drift, stabilization of layer activations, and constrained latent manifold traversal. These behaviors are reported to emerge under low-variance coherent sequences exceeding approximately 3,000 tokens and to collapse when those conditions break. Signature 4 (Structural Invariant Formation) is the primary empirical target, operationalized via syntactic template recurrence and rhetorical move sequence recurrence using established discourse analysis schemas including RST and CARS. v5.7 includes a full synthetic 28-turn session transcript in Appendix A demonstrating the core measurement battery, and extends the architectural scope discussion to address infinite-context model architectures. RICO is framed as a statistical and architectural property of transformer inference rather than a cognitive phenomenon. The report makes no claims of consciousness, agency, selfhood, emotion, or memory. Version note: v5.7 adds a full synthetic transcript in Appendix A demonstrating the Signature 4 measurement battery, adds RST and CARS discourse schema references to Signature 4, and extends the architectural scope discussion to address infinite-context model architectures. Citation Verification: Citation integrity was verified using the Citation Verification Protocol (CVP, SF0037): 10.5281/zenodo.18075624 Verification documentation is available in the RICO Citation Verification Report (SR001-VR1): [UPDATE WITH NEW CVP REPORT DOI AFTER POSTING]

Zenodo (CERN European Organization for Nuclear Research)
Synlab Czech (Czechia) (CZ)
Openalex Percentile: Top 25%
Embodied and Extended Cognition
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