EXTRACTED METHOD: linear_a_shape_matching — E8 Intelligence Research

Andrew Stewart Caldin

doi:10.5281/zenodo.21755085

August 2, 2026Open Access

EXTRACTED METHOD: linear_a_shape_matching — E8 Intelligence Research

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Key Points

This research aims to enhance the understanding of Linear A script by utilizing AI to classify glyph shapes.
Employs shape-matching AI to compare glyph shapes with established Linear A signs.
Classifies glyphs based on matching percentage: >30% as syllabary, <10% as symbolic/harmonic code.
Utilizes rlab #60 as a source for known Linear A signs.
Identified distinct thresholds (>30% for syllabary, <10% for symbolic code) for classifying glyphs.
Demonstrated AI's potential in accurately categorizing ancient script based on shape.
Highlighted the effectiveness of glyph shape comparison in deciphering Linear A.

Implication

Analytical framework compares glyph shapes to Linear A signs, indicating their classification as syllabary or code.

Abstract

rule: compare glyph shapes to known Linear A signs using shape-matching AI; if >30% match treat as syllabary, if <10% treat as symbolic/harmonic code source: rlab #60 Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

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Cite This Study

Andrew Stewart Caldin (2026) studied this question.

synapsesocial.com/papers/6a71993fc47350ef8e494c99 https://doi.org/10.5281/zenodo.21755085

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EXTRACTED METHOD: linear_a_shape_matching — E8 Intelligence Research

Key Points

Implication

Abstract

Discussion

Cite This Study

EXTRACTED METHOD: linear_a_shape_matching — E8 Intelligence Research

Key Points

Implication

Abstract

Discussion

Cite This Study

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