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ZENODO
Journal . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Journal . 2026
License: CC BY
Data sources: Datacite
ZENODO
Journal . 2026
License: CC BY
Data sources: Datacite
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SCALPEL Heart: Cellular Regeneration via Semantic Ricci Flow

Authors: Pérez Contreras, Benjamín Felipe;

SCALPEL Heart: Cellular Regeneration via Semantic Ricci Flow

Abstract

e present the SCALPEL Heart, a regenerative algorithm inspired by cardiac physiology that implements semantic Ricci Flow for dataset curation. The heart “beats” generating cells—geometrically coherent k-neighborhoods—and distributes them through the data manifold. The cardiac rhythm adapts to the disorder parameter ρ: higher stress induces faster heartbeat and more aggressive regeneration.Key contributions: 1. Formalization of cells as k-neighborhoods in Hilbert space 2. Implementation of supervised Ricci Flow for cell optimization 3. Adaptive pumping algorithm based on disorder level 4. Empirical validation: 100% of datasets show ∆ρ < 0 (cross-validated with [CC-Theorem 8.1]) 5. Connection to the Semantic Tolerance Law

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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
Average
Average