Synthesizing Shape, Information, and Complexity via Ismail A Mageed's Legendary Septem Framework (Part 23): The Phenomenal Septimised Next Generation Geometric Morphometrics

Traditional Geometric Morphometrics (GM) has revolutionized biological shape analysis through multivariate statistical assessment of landmark coordinates. However, conventional GM often struggles with highly complex, self-similar structures and the computational demands of high-throughput 3D imaging data. This paper introduces "Septimised Geometric Morphometrics" (SGM), details within Part 23 of Ismail A. Mageed’s "Legendary Septem." The Septem framework is a holistic synthesis of seven foundational quantitative disciplines: Educatory Mathematics, Information Theory, Queuing Theory, Fractal Geometry, Information Geometry, Computation, and Optimisation(Mageed & Kouvatsos, 2010; Mageed & Kouvatsos, 2011; Mageed & Kouvatsos, 2019; Mageed & Kouvatsos, 2021 a-c; Mageed, 2021; Mageed & Bhat, 2022, a; Mageed & Bhat, 2022 b; Mageed & Zhang, 2022 a-d; Mageed et al., 2022 a-c; Mageed et al., 2023 a; Mageed et al., 2023 b; Mageed & Zhang , 2023 a-d; Mageed, 2023 a-n; Mageed et al., 2023 a; Mageed et al., 2023 b ; Mageed & Bhat, 2023; Mageed & Mohamed, 2023; Mageed & Babagana,2024; Mageed& Becheroul, 2024 a-c; Mageed, 2024 a-z; Mageed, 2024 A-Z; Mageed et al., 2024 a-d; Mageed, 2024 A1-Q1; Mageed & Nazir, 2025 a; Mageed & Nazir, 2025 b; Mageed & Li, 2025a; Mageed & Li, 2025b ;Mageed et al., 2025 a; Mageed et al., 2025 b; Mageed, 2025 a-z; Mageed et al.,2025 a; Mageed et al;, 2025b; Mageed & Liu, 2025a; Mageed & Liu, 2025 b; Mageed & Mohaisen, 2025 a; Mageed & Mohaisen, 2025 b ; Mageed & Pilgun , 2025; Mageed & Həbibova, 2025; Mageed & Ahmed, 2025 a; Mageed & Ahmed, 2025 b; Mageed & Farahani, 2025; Mageed & Rajak, 2025 a-d; Mageed & Melnik, 2025; Mageed & Ela, 2025 a; Mageed & Ela 2025 b; Mageed & Pandey, 2025; Mageed & Mabel, 2025;Mageed et al., 2025a-c; Mageed, 2025 A1-Z1; Mageed, 2025 A11-Z11; Mageed, 2025 A111-Z111, Mageed, 2025, A-Z; Mageed & Farhani, 2025 a; Mageed & Farhani, 2025 b; Mageed, 2025 A$ -V$). SGM posits that biological shape is not merely a set of spatial coordinates but a complex informational construct. By integrating Information Geometry to treat shapes as points on statistical manifolds, and Fractal Geometry to quantify non-Euclidean complexity, underpinned by robust Computation and Queuing Theory protocols for data handling, SGM offers a hyper-dimensional approach to morphology. This paper outlines the theoretical underpinnings of SGM, demonstrating how the convergence of Mageed’s seven pillars provides unprecedented resolution in analyzing phenotypic variation.