Predictive Bioharmonics: A Domain-Invariant Algorithm for Identifying Global Structural Compatibility
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| Format: | Recurso digital |
| Sprache: | Englisch |
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Zenodo
2025
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| _version_ | 1866901657849167872 |
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| 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> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18057339 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| 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 |