Constructing Executable Analytical Knowledge Representations for Meta-Analysis Synthesis Using an Agentic Harness

Meta-analysis synthesis highlights a fundamental challenge in knowledge-based scientific analysis: structured evidence does not by itself represent the analytical knowledge required for executable computation. Decisions about evidence assignment, analytical contrasts, outcome and time-point alignment, effect-size formulation, and methodological admissibility must be explicit before statistical execution. Existing automated approaches often embed these decisions in model outputs, generated code,

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ethics.ai (3 August 2026), “Constructing Executable Analytical Knowledge Representations for Meta-Analysis Synthesis Using an Agentic Harness,” evidence record 15905, https://ethics.ai/record/15905 (originally published by arXiv).

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