Predictive Bioharmonics: A Domain-Invariant Algorithm for Identifying Global Structural Compatibility

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1. Verfasser: Fries, Tess
Format: Recurso digital
Sprache:Englisch
Veröffentlicht: Zenodo 2025
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_version_ 1866901657849167872
author Fries, Tess
author_facet Fries, Tess
contents <p dir="ltr">In many scientific and technological domains, researchers informally refer to a “holy grail”: a solution, configuration, or state that appears to resolve a problem completely, without introducing new trade-offs. Despite the ubiquity of this concept, no domain-invariant, operational definition exists that allows such states to be identified, tested, or falsified using data.</p> <p dir="ltr">This paper proposes a scale- and domain-invariant algorithmic framework for identifying candidate “holy grail” states in dynamical systems. Rather than treating the holy grail as an object, goal, or outcome, the framework models it as a structural compatibility condition: a state in which further optimization, decision refinement, or intervention no longer improves the expected outcome.</p> <p dir="ltr">The framework is explicitly non-deterministic and does not claim proof or completeness. It provides a practical decision procedure that can be applied to real-world data across biological, physical, technological, medical, and abstract systems.</p>
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spellingShingle Predictive Bioharmonics: A Domain-Invariant Algorithm for Identifying Global Structural Compatibility
Fries, Tess
Predictive Bioharmonics
dynamical systems
decision termination
structural compatibility
optimization exhaustion
domain invariance
scale invariance
IVF decision-making
system stability
algorithmic stopping criteria
<p dir="ltr">In many scientific and technological domains, researchers informally refer to a “holy grail”: a solution, configuration, or state that appears to resolve a problem completely, without introducing new trade-offs. Despite the ubiquity of this concept, no domain-invariant, operational definition exists that allows such states to be identified, tested, or falsified using data.</p> <p dir="ltr">This paper proposes a scale- and domain-invariant algorithmic framework for identifying candidate “holy grail” states in dynamical systems. Rather than treating the holy grail as an object, goal, or outcome, the framework models it as a structural compatibility condition: a state in which further optimization, decision refinement, or intervention no longer improves the expected outcome.</p> <p dir="ltr">The framework is explicitly non-deterministic and does not claim proof or completeness. It provides a practical decision procedure that can be applied to real-world data across biological, physical, technological, medical, and abstract systems.</p>
title Predictive Bioharmonics: A Domain-Invariant Algorithm for Identifying Global Structural Compatibility
topic Predictive Bioharmonics
dynamical systems
decision termination
structural compatibility
optimization exhaustion
domain invariance
scale invariance
IVF decision-making
system stability
algorithmic stopping criteria
url https://doi.org/10.5281/zenodo.18057339