Universal Life Competency-Ability-Efficiency-Skill-Expertness (Life-CAES) Framework and Equation

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Authors: Mokhdum Azam Mashrafi Mokhdum Azam Mashrafi
Cited by: 0

Abstract

Living systems demonstrate substantial variability in growth, reproduction, productivity, resilience, andsurvival, even when exposed to broadly similar environmental resource inputs. Classical biologicalmodels attribute such variability to domain-specific mechanisms—such as metabolic rate, nutrientuptake efficiency, genetic potential, and hormonal regulation—but no existing framework quantitativelyintegrates these mechanisms into a unified cross-kingdom performance model. This study introducesthe Universal Life Competency–Ability–Efficiency–Skill–Expertness (Life-CAES) framework as a systems-biology formulation that explains biological performance as the coupled outcome of resourceacquisition and biochemical conversion efficiency. Grounded in mass conservation principles, rate-limited physiological processes, biochemical competency, and absorption capacity, the Life-CAESequation defines performance as a function of organismal mass, uptake velocity, absorption capacity,internal conversion efficiency, and time-dependent mass assimilation. The framework is biologicallyconservative and dimensionally interpretable, and it provides an empirically testable basis for cross-species comparison of growth and productivity. The model is applicable to plants, animals, humans, fish,insects, microorganisms, and other living systems, offering a unifying conceptual and mathematical toolfor interpreting why organisms with similar external inputs can exhibit remarkably different biologicaloutcomes. As such, the Life-CAES framework presents a novel step toward predictive, integrative, andcomparable biological performance modeling across diverse life forms...... Please check the attachment for details

Fields of Study & Subjects

Physiological and biochemical adaptations Sustainability and Ecological Systems Analysis Ecology and Vegetation Dynamics Studies

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
15 January 2026