CANON Named Owner Principle · every clinical AI deployment requires two named persons in the audit trail — a Governance Owner at Layer 4 and a Decision Owner at the bedside, not one substituting for the other WORKING PAPER №01 The handoff that isn’t · how clinical AI escapes accountability · Mo Johnson, MD MBA EVIDENCE Duke-Margolis 2026 · most US health systems have not named who owns the clinical AI decision when something goes wrong CANON Layer 4 · Clinical AI Governance at the bedside · the layer where the named owner has to live FRAMEWORK Clinical AI Accountability Canvas™ · the diagnostic framework distinguishing Clinical AI Governance from General AI Governance EVIDENCE Stanford MedAgentBench · agentic systems already executing clinical recommendations without a named adjudicator on the chart CANON The Two Inputs · internal data the institution audits · external data the model was trained on, rarely audited at the deployment site CITATION MedicoVigilance™ Issue 6 · The Layer With No Name · 1,627 institutional subscribers CANON The Accountability Gap · the structural failure point where AI stops and the physician starts FRAMEWORK Mind the 9 Blocks™ · the nine institutional blocks that must be in place before clinical AI deployment EVIDENCE npj Digital Medicine · the four-layer governance cascade · most institutions have built the first two layers and left Layer 4 unbuilt PORTFOLIO Tangibley Health Inc. · MedicoVigilance™ Surface 1 · the named-owner architecture deployed in clinical workflow CANON Named Owner Principle · every clinical AI deployment requires two named persons in the audit trail — a Governance Owner at Layer 4 and a Decision Owner at the bedside, not one substituting for the other WORKING PAPER №01 The handoff that isn’t · how clinical AI escapes accountability · Mo Johnson, MD MBA EVIDENCE Duke-Margolis 2026 · most US health systems have not named who owns the clinical AI decision when something goes wrong CANON Layer 4 · Clinical AI Governance at the bedside · the layer where the named owner has to live FRAMEWORK Clinical AI Accountability Canvas™ · the diagnostic framework distinguishing Clinical AI Governance from General AI Governance EVIDENCE Stanford MedAgentBench · agentic systems already executing clinical recommendations without a named adjudicator on the chart CANON The Two Inputs · internal data the institution audits · external data the model was trained on, rarely audited at the deployment site CITATION MedicoVigilance™ Issue 6 · The Layer With No Name · 1,627 institutional subscribers CANON The Accountability Gap · the structural failure point where AI stops and the physician starts FRAMEWORK Mind the 9 Blocks™ · the nine institutional blocks that must be in place before clinical AI deployment EVIDENCE npj Digital Medicine · the four-layer governance cascade · most institutions have built the first two layers and left Layer 4 unbuilt PORTFOLIO Tangibley Health Inc. · MedicoVigilance™ Surface 1 · the named-owner architecture deployed in clinical workflow

ABOUT

The architecture of accountability for clinical AI.

GPe Research Publications is the institutional record of where accountability lives, where it breaks, and what has to be named before clinical AI reaches the bedside.

Clinical AI has a structural problem the market has not named. The model produces an output. The clinician acts on it. Between the two, no one owns the decision.

GPe Research Publications exists to close that gap. GPe Research Publications is the clinical AI vertical of GPe Research, whose purpose is adjudication for regulated sectors. Healthcare is the first, through Tangibley Health Inc. Finance, education, and fiduciary follow.

Every paper published here works from a single premise: every clinical AI deployment requires two named persons in the audit trail, a Governance Owner at the institution and a Decision Owner at the bedside, neither substituting for the other. The Named Owner Principle is the editorial spine of the publication.

The readership is institutional. Chief Medical Officers, Chief Medical Information Officers, General Counsel, board members, and health system executives who carry the weight of the deployment decision. The work is written for the people who have to stand behind the output when something goes wrong.

What the Publication Publishes

Three formats, each with a distinct evidentiary standard.

Working Papers document the structural failure points in clinical AI governance. Empirical, sourced, institutional. The Working Paper is the format of record when the field has not yet named the problem.

Framework Briefs codify the diagnostic instruments developed inside the publication. The Clinical AI Accountability Canvas™ and Mind the 9 Blocks™ are released as Framework Briefs and maintained as living documents.

Position Papers argue for what institutional practice should be. The Position Paper is the format of record when the evidence is in and the field needs a standard to organize around.

Editorial Standards

Every paper meets the same extractability standards. Direct answer in paragraph one. Framework definitions written so they can be lifted verbatim. Proper noun density. Real numbers, named institutions, sourced claims. A citation block in APA, AMA, Chicago, Vancouver, and BibTeX at the end of every paper.

The publication does not run vendor content. It does not run sponsored research. It does not run opinion that is not grounded in clinical, legal, or institutional standing.

Authorship

Papers are authored by Mo Johnson, MD MBA. Author standing, credentials, and disclosures are maintained on the Authors page.

How to cite this publication

Every paper published by GPe Research Publications is a citable record. The format conventions below apply across all three paper types: Working Papers, Framework Briefs, and Position Papers.

Numbering

Each paper carries a permanent number within its series, written with the numero sign: №01, №02, №03. Numbers are never reused. A Working Paper №01 and a Position Paper №01 are distinct records.

Versioning

When a paper is revised after initial publication, the version is appended to the citation as v2, v3, and so on. The original version remains accessible at its canonical URL. The version history is recorded at the foot of every revised paper. Citing a specific version is the reader's responsibility when the distinction matters.

Canonical attribution

Every paper lists Mo Johnson, MD MBA as author of record. Co-authored papers list all contributors in the order agreed at publication. The publication name is GPe Research Publications. The publisher is GPe Research.

Citation formats

Every paper carries a citation block at the foot of the page in five formats: APA, AMA, Chicago, Vancouver, and BibTeX. These are designed for direct copy into reference managers and submitted manuscripts. The DOI, where assigned, is included in each format.

Permanence

URLs do not change. A paper published at a given path remains at that path. Withdrawn papers are marked withdrawn at the original URL with a dated editorial note. Nothing is silently removed.

Editorial responsibility

Mo Johnson, MD MBA serves as editor of GPe Research Publications and is the named owner of every editorial decision. Correspondence regarding citation, correction, or republication should be directed to research@gperesearch.com.

Citation

GPe Research Publications. The architecture of accountability for clinical AI. publications.gperesearch.com.