What the source specifies
A proposed gated scoring system combines retrieval relevance, evidence, trust, entity clarity, usefulness, context, feedback and corroboration, with risk and competition penalties.
Equations and variants
Every visible complete mathematical relation has a linked record, including parameter definitions, constraints, decorative corner equations and repeated formula variants. The original images and full reading copies are available through the source links.
Source findings and limits
The repeated shorthand AI_VIS(...) = Final Visibility Score and p* = argmax_p AI_VIS(...) restate the master score and argmax; they do not introduce distinct formulas.
COMPETITION and REDUNDANCY appear in the master expression and quick-view prose, but no independent computational formula for either is shown.
The image is a project artifact proposing an AI-visibility framework. Named platforms in its output list are claims of intended application, not evidence of adoption or empirical performance.
Equations in this build
14 linked mathematical records. Each opens its notation, interpretation and source.
Gated AI visibility score
A gate multiplies a weighted sum of eight positive scoring factors and three suppression factors. The compact transcription names the visible factors without inventing uncertain…
Softmax source-selection probability
The candidate score is exponentiated after division by a temperature, and divided by the sum of exponentiated candidate scores.
Choose a source maximizing the proposed visibility score
The argmax operator returns the candidate source p whose AI_VIS score is largest for the specified query, claim, user context, time, and location. The starred p* denotes the…
Eligibility gate
Combines crawl, index and retrieval eligibility as a product.
Gate suppression condition
A zero gate suppresses the visibility score regardless of the weighted factors.
Findability factor
Combines lexical retrieval, vector similarity, query intent, entity overlap, and topical relevance.
Claim-support factor
Adds positive evidence and answerability signals and subtracts contradiction.
Trust factor
Combines authority and reliability labels. The poster does not define common units or transformations for adding these signals.
Entity factor
Combines entity prominence, consistency, knowledge-graph score, sameAs support, and schema clarity.
Usefulness factor
Adds information gain, completeness, recency and experience signals for the candidate query.
Context factor
Combines the query and user-context fit dimensions listed in the image.
Feedback factor
Combines click-through and engagement-style signals with short-click and pogo-sticking penalties.
Cross-source corroboration factor
The panel links source support and source trust in a summed corroboration calculation.
Risk factor
Adds negative-content and access-risk labels into the risk quantity that is penalized in the master score.