BU81 Stock-Side Manifestation of the Universal Co-Admissive Medium under B_U Depth Curse, Cross-Domain Structural Resonance, Technological Mismatch, Structural-Attribute Matching Platform, and Patent / Result-Library Awakening

Many industries urgently need technologies that have long remained dormant in another industry’s patents, papers, failed experiments, edge data, prototypes, and immature results. BU81 develops this problem as the stock-side manifestation of the universal co-admissive medium under B_U. Its central claim is direct: technology transfer often fails because systems search by use-case labels, industry categories, document titles, keywords, project narratives, or market stories, while the real correspondence exists at the level of structural attributes. Once technical results and industrial bottlenecks enter the same structural-attribute space, dormant technologies can form linkages, reveal value, and accelerate transformation. BU81 solves the depth curse and technological mismatch; through structural-attribute matching, it triggers cross-domain structural resonance and awakens patent / result libraries. The depth curse names the structural weakening of later-stage contributions when deep processes lack identity anchoring, weak persistence, soft-link expression, and friction-cost representation. In deep learning this appears as vanishing gradients, exploding gradients, late-layer contribution decay, and weakened influence on the final output distribution. In organizations, research systems, industrial chains, and social collaboration, the same structure appears as late-stage decision failure, non-accumulative research, policy transmission loss, or marginalization of later participants. The root problem is structural incompleteness: systems fail to preserve weak but persistent influence. BU81 then reframes cross-domain structural resonance as a practical mechanism. A deep result in one domain may lower the entropy cost of reaching a stable structure in another domain when identity anchoring, weak persistence, soft links, and friction-cost expression exist. This is not simple information sharing, model reuse, or surface analogy. It is structural recognition across domains: different fields may carry attenuated versions of the same stability pattern. A result that appears useless inside one field may act as the missing structure inside another field’s upgrade bottleneck. The file proposes a Cross-Domain Structural Matching Platform (CDSMP). The platform indexes technical results as structural-attribute vectors \mathcal S(T) and industry bottlenecks as missing-structure vectors \mathcal M(B). Its core task is candidate discovery: reduce blind search, rank possible structural correspondences, estimate friction cost, and route candidates toward verification. It does not guarantee commercial success, replace experts, or endorse technologies. It gives experts a lower-entropy candidate field. BU81 also treats patent libraries and result libraries as awakened structural probes. Under text-based indexing, old results remain archived. Under structural indexing, they become a distributed sensor array across the technical possibility space. The historical possible-but-not-manifested gap and the Ajinomoto ABF case show the same principle from two angles: technical fragments may exist long before their invention standing settles, and a capability born in one field can become a critical substrate in another. BU81 pairs with BU76. BU76 manifests future-side standing conditions through demand preloading and pre-feedback. BU81 manifests stock-side standing conditions by re-indexing existing results and dormant capabilities. Together, they operationalize BU80: new standing positions arise when latent structures form linkages, pay friction costs, pass verification, and settle into application reality.