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Study Defines the Threshold Where AI Systems Stop Treating a Brand as Replaceable

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Theorem 1 of The Ontological Dominance Papers specifies four conditions required for a business to achieve durable authority in AI citations.

JOHNSTON, Iowa - Rezul -- Big House Enterprise has published Theorem 1 of The Ontological Dominance Papers, formalizing what the firm calls Full Spectrum Dominance - a threshold condition under which a business's authority signal construction outpaces both natural decay and competitive interference across AI training cycles. The paper specifies that Full Spectrum Dominance requires a citation probability of at least 0.75 across a defined set of competitive queries, and identifies four conditions that must hold simultaneously to sustain it.

The theorem builds on earlier findings from Big House Enterprise showing that most authority signals are vulnerable to competitive equalization. This paper asks a narrower question: what would it take for a business's position to become effectively unassailable rather than merely ahead.

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"Being ahead and being dominant are different states," said Joseph Byrum, Founder of Big House Enterprise and author of the paper. "Ahead means a competitor with more budget can catch up next quarter. Dominance means the math stops working in their favor even if they try."

The analysis identifies temporal depth — how long an entity's authority signals have existed — and vocabulary sovereignty — ownership of the terminology used to describe a category — as the two advantages the research found resistant to equalization, regardless of competitor spend. The findings are supported by mathematical analysis and an agent-based simulation run across more than 5,000 parameter combinations.

"Money can buy volume," Byrum said. "It can't buy the fact that you were the first authoritative source AI systems learned to associate with a term. That's the part competitors can't simply outspend."

Big House Enterprise plans to release the next paper in the program, addressing how businesses achieve accurate representation in the specific queries their actual customers use, in the coming weeks.

Follow the release of the papers on the website: https://bighouseenterprise.com

Source: Big House Enterprise

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