A Normative Meta-Level Methodological Framework for Scientific Research Based on HDCST Principles and Controlled Use of AI Tools

Normative, meta-level methodological framework for scientific research under uncertainty and AI-assisted workflows. The framework prioritizes stability, phase locking, ethical control, and misuse resistance over optimization or performance guarantees. It introduces explicit entry conditions (G0), error-first analysis, and strict prohibition of retroactive rationalization.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-01-06
DOI
https://doi.org/10.5281/zenodo.18164097
Primary Topic
Scientific Computing and Data Management
Type
article
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article

A Normative Meta-Level Methodological Framework for Scientific Research Based on HDCST Principles and Controlled Use of AI Tools

Zvonko Vulicevic
Zenodo (CERN European Organization for Nuclear Research)
Scientific Computing and Data Management
article

A Normative Meta-Level Methodological Framework for Scientific Research Based on HDCST Principles and Controlled Use of AI Tools

Zvonko Vulicevic
article en

Abstract

Normative, meta-level methodological framework for scientific research under uncertainty and AI-assisted workflows. The framework prioritizes stability, phase locking, ethical control, and misuse resistance over optimization or performance guarantees. It introduces explicit entry conditions (G0), error-first analysis, and strict prohibition of retroactive rationalization.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 94%
Scientific Computing and Data Management
DOIOpen Access PDFOpenAlex
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A Normative Meta-Level Methodological Framework for Scientific Research Based on HDCST Principles and Controlled Use of AI Tools — Zvonko Vulicevic · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS