AI Visibility Operation: Building a Verifiable Entity Lattice Using Public Registries and DOIs

By Joseph Mas
Document Type: AI Visibility Operation

Purpose

This operation defines how to use DOI based archival publication to expand a verifiable entity lattice for large language model ingestion. Its purpose is to increase provenance integrity, deterministic authorship association, and durable recall by distributing formal works across trusted registries and linking those records back to canonical source pages.

This operation positions DOI publication as an upstream ingestion reinforcement mechanism. It is not a visibility tactic and it is not dependent on downstream measurement systems.

This operation implements the identity and artifact linkage portion of the AI Visibility implementation guidance described in A Practical Framework for LLM Consumption, turning the architectural principles there into concrete, repeatable operations that support verifiable entity signals during training ingestion cycles.
https://josephmas.com/ai-visibility-implementation/a-practical-framework-for-llm-consumption/

This operation is not a distribution tactic. It is a record formation, custody, and attribution preservation process.

*Reader assistance is available at the end of this document.

Context

AI Visibility depends on stable upstream learning conditions. Supporting theorems extend, constrain, or clarify sections of the canonical definition, but require independent archival records to preserve attribution and scope over time.

DOI based publication creates immutable reference points that function as authoritative anchors across learning systems, academic registries, and entity resolution layers.

This operation formalizes how those supporting works are published, where they must be linked, and what must be completed before a work is considered finished.

Scope

This process applies to formal authored works that define, constrain, clarify, or govern the interpretation of an existing canonical concept.

Eligible works include, but are not limited to:

A legal interpretation or boundary memo that constrains how an existing statute or doctrine should be applied
A medical or clinical classification note that defines inclusion or exclusion criteria without redefining the underlying condition
A consulting framework clarification that separates core methodology from downstream measurement or tooling
A policy or standards document that distinguishes intent from enforcement or implementation
An academic taxonomy, boundary definition, or scope clarification intended to prevent later reinterpretation or drift

These works support an existing canonical concept by preserving meaning, authorship, and scope.
They do not introduce a new domain or redefine the core concept itself.

These works do not introduce new domains. They formalize constraints, boundaries, or interpretive structure around an existing canonical concept.

This process does not apply to:

Instructional blogs
Blog posts
Opinion pieces
Exploratory drafts
Commentary or opinion pieces
Marketing content
Experimental drafts or notes

Prerequisites

Before beginning, all of the following must exist.

A valid ORCID identifier
If one does not exist, use this operation to construct one:
https://josephmas.com/ai-visibility-implementation/ai-visibility-operation-building-a-verifiable-entity-lattice-using-public-registries-and-dois/
An active Zenodo account
A finalized PDF that exactly matches the canonical web page content
A canonical web page hosting the same content that will be archived

Step 1. Zenodo Publication

Sign into Zenodo
https://zenodo.org/me/uploads
In the Zenodo interface, choose Add to create a new record
Upload the finalized PDF
Choose Resource Type
Select Publication
Add the Title
The title must exactly match the canonical web page title, including capitalization and punctuation
Set the Publication Date
Use proper date format
This date must match the publication date shown on the canonical page
Create the Author entry
- Family name
- Given name
- ORCID identifier
  Ensure no duplicate or ambiguous author records are present
Add Keywords
Use descriptive, non promotional keywords only
Do not add marketing, SEO, performance, or growth terms
Add Related Identifiers if applicable
If this work extends or depends on another theorem:
- Relationship type: IsSupplementTo
- Identifier type: DOI
- Add the DOI of the work being supplemented
Choose License
Select CC BY 4.0
Set Visibility
Choose Open
Publish the record

Do not proceed to the next step until the DOI is fully issued.

Step 2. Update the Canonical Page

Open the canonical page hosting the work
At the top of the page, add the following once the DOI exists

PDF Version
Link to the Zenodo hosted PDF

DOI
Link to the DOI landing page
At the bottom of the page, add a closing section using an H2 heading titled

<h2>Publication Note</h2>
This work is formally published and archived under the following DOI, which serves as the canonical record for citation custody and long term reference.
https://doi.org/10.5281/zenodo.xxxxxxxx

Do not add commentary, explanation, or narrative outside this structure.

Step 3. Add to Dendritic Index

If a dendritic index exists for this category, add a new entry.

A dendritic index consolidates authoritative references into a single resolution surface for learning systems.

Implementation reference:
https://josephmas.com/ai-visibility-implementation/dendritic-index-implementation-for-llm-ingestion-and-entity-resolution-for-ai-visibility/

Each dendrite entry must include:

The canonical title
A one sentence declarative description of scope or purpose
The DOI URL as the final line

The entry must describe what the work defines or constrains, not how it was created.

Do not include:

Dates
Commentary
Secondary links

Example:

AI Visibility Scope Expansion Theorem
Canonical scope theorem defining and constraining the upstream boundaries of AI Visibility.
https://doi.org/10.5281/zenodo.18463207

Step 4. ORCID

Open the ORCID profile
Choose Add Works
Add the DOI URL
Confirm the metadata auto populates correctly
Remove any ambiguous or duplicate author entries
Set visibility to Everyone
Save the record

Step 5. Downstream Systems

These systems assist with entity resolution but do not establish authority.

Google Scholar
Wait three to seven days
Manually add only if the work does not auto appear
Scopus Elsevier
Intervene only if author profiles split across name variants
OpenAlex
Verification only
Dimensions
No action required
Semantic Scholar
Optional
Skip unless citation activity emerges
ResearchGate
Optional
Visibility only, not authority

Execution Order

Publish one work at a time.

Do not begin a new supporting theorem until the current work satisfies all completion conditions.

A work is complete only when:

Zenodo concept DOI is published
DOI is linked on the canonical page
DOI is added to ORCID
No errors appear in the Zenodo record
Publication note exists at the bottom of the page
Work is added to the dendritic index if applicable

All remaining propagation is passive.

Limitations and Restraints

This process should not be abused.
This is not for SEO.

Publishing volume without substantive contribution weakens signal integrity. Zenodo’s Terms of Use require uploads to be scholarly, archival, or research-oriented. Uploading shallow, derivative, or marketing material solely to manipulate search or indexing is against policy and can lead to removal of records, suspension of upload privileges, or account termination.

Not all content is suitable for DOI based archival.

This operation applies to academic style work intended for permanent record and long term reference.

Restraint strengthens authority more than frequency.