Evidence-Graded Evaluation for Autonomous Agents: A Fail-Closed Methodology

Working paper v0.1. Proposes an evidence-graded, fail-closed evaluation methodology for autonomous agents: an E0-E4 evidence scale, a gate that refuses to pass on insufficient evidence, scope binding, and negative controls. Includes a case study of a 100/100 self-score versus a 89/100 internal audit traced to an empty test suite and version drift.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-08
DOI
https://doi.org/10.5281/zenodo.24052276
Primary Topic
Safety Systems Engineering in Autonomy
Type
preprint
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preprint

Evidence-Graded Evaluation for Autonomous Agents: A Fail-Closed Methodology

Xinghua (Steven Zhao) Zhao
1 links
Zenodo (CERN European Organization for Nuclear Research)
Safety Systems Engineering in Autonomy
preprint

Evidence-Graded Evaluation for Autonomous Agents: A Fail-Closed Methodology

Xinghua (Steven Zhao) Zhao
preprint en

Abstract

Working paper v0.1. Proposes an evidence-graded, fail-closed evaluation methodology for autonomous agents: an E0-E4 evidence scale, a gate that refuses to pass on insufficient evidence, scope binding, and negative controls. Includes a case study of a 100/100 self-score versus a 89/100 internal audit traced to an empty test suite and version drift.

Zenodo (CERN European Organization for Nuclear Research)
Safety Systems Engineering in Autonomy
DOIOpen Access PDFOpenAlex
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Evidence-Graded Evaluation for Autonomous Agents: A Fail-Closed Methodology — Xinghua (Steven Zhao) Zhao · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS