MJos Predictive Model | First manifestation of the Bangel Language
New project sequence · proposed bindings
Associative recall, relational discrimination and bounded source-grounded diagram overlays.
MJ Neural Net / Yellow
MJos Predictive Model | First manifestation of the Bangel Language
MJ Physics Engineering | Owned and operated by Michael Bangel | Clearwater, Florida
INFORMATION FLOW BLUEPRINT
MJ Neural Net
Declared source + context
-> input shape / unit / evidence review
-> Run bounded association; preserve missing features; compare entity/relation/context; bind independent review.
-> result + explicit status + source reference
-> independent authority review when an external effect is requested
MEASUREMENT LABELS
- Feature: Missing(reason) | Known(Real)
- Nodes: n1…n9
- Memory: identity + pattern + relation + context
- Review: request hash + status
- r0: PROVISIONAL
DIAGRAM RULE
This is a new logical flow, not physical geometry, an approved circuit or a calibrated scale. Existing Yellow picture templates are reference geometry and may conflict with their titles. YP-093 is a known example requiring review. No geometry-to-language equivalence is inferred from a picture alone.
EVIDENCE LIMITS
- Engineered computational model, not hippocampal biology or general natural-language prediction.
- Lowercase r0 remains provisional and distinct from uppercase R0.
- Synthetic comparison shows a recall/coverage tradeoff; not field accuracy or equal-coverage benefit.
- Diagram geometry and command mapping must retain separate namespaces.