Read the equation
The candidate score is exponentiated after division by a temperature, and divided by the sum of exponentiated candidate scores.
Its role in the build
The Universal AI Visibility Equation
Terms & definitions
| Term | Meaning in this source |
|---|---|
| p | Page / website / source (the candidate). |
| q | User query. |
| c | Claim the statement needs to support. |
| u | User context, including location, device, language, personalization and history when used. |
| t | Time: current time, freshness needs and topic volatility. |
| l | Location: geographic location, service area and proximity. |
| S | Selected sources already chosen, used for diversity control. |
| τ | Temperature controlling selection sharpness versus diversity. |
How it works
Read P(select p | q,c) as the quantity being defined or updated by this relation.
Applies an exponential factor. The exponent determines its real scaling or, for a complex exponent, its phase.
Use this version’s variable definitions and update order. The same symbol may be assigned a different meaning in another build.
Assumptions & limits
This is a normalized selection model proposed by the poster. It does not establish that any named external platform uses this rule.
The upper typeset denominator appears to print p rather than p_j although its sum is over j. The lower monospaced version appears to include p_j, with some small adjacent punctuation degraded. This transcription follows the lower candidate-index version and records the upper discrepancy.
A defined candidate set, nonzero temperature, and finite scores are needed to evaluate the expression.
Original context
Read the surrounding source passage
The Universal AI Visibility Equation: The candidate score is exponentiated after division by a temperature, and divided by the sum of exponentiated candidate scores.
Exact original notation
P(select p | q,c) = exp(AI_VIS(p,q,c,u,t,l)/τ) / Σ_j exp(AI_VIS(p_j,q,c,u,t,l)/τ)
Related builds
Sources & provenance
P(select p | q,c) = exp(AI_VIS(p,q,c,u,t,l)/τ) / Σ_j exp(AI_VIS(p_j,q,c,u,t,l)/τ)