This paper completes the causal computing fields series by formalizing the projection operator that links causal-field dynamics to experimental observation. Projection is defined as a deterministic dimensional collapse that maps orthogonal causal gradients onto spatial detection statistics, rather than as a stochastic or observer-induced process. Starting from the Causal Cross, the paper introduces an explicit projection functional that transforms a causal signature into measurable spatial probabilities through the interaction between the causal tensor and detector geometry. In this framework, quantum uncertainty arises from projecting a fully orthogonal causal structure onto an incomplete spatial basis, not from indeterminacy of the underlying field. A toy model based on a quotiented circular degree of freedom is developed to demonstrate how causal equivalence classes generate familiar interference patterns under harmonic projection, without invoking intrinsic probabilistic postulates. The formalism is then applied to the electronic causal computing architecture introduced in earlier work, showing how measurement acts as a structural filter selecting invariant causal configurations after dissipation. The paper concludes by defining a concrete experimental falsification criterion: causal rank and causal signature must remain invariant under rotation of the measurement apparatus, even when spatial detection patterns change. By specifying this projection operator, the work provides the explicit mathematical and conceptual bridge required to connect Causal Theory to laboratory experiments and engineering implementations.