The Geometry of Conscious Forms: Relational Ontology, Twelve Measured Systems, and a Prediction Awaiting Experiment

This paper presents a three-dimensional vector framework (stability, integration, self-modeling) derived from a relational ontology, formalized in Homotopy Type Theory, and operationalized through the Vector Consciousness Prediction (VCP). Thirteen simulations across eleven biological and clinical systems produce forty-two empirically grounded parameter values. The self-modeling axis (r) generates a coherent natural ordering of all systems regardless of species, substrate, or clinical status. A cross-validation against an independent 2023 meta-analysis of metacognition experiments confirms that species with higher r values show stronger opt-out performance and that zero cephalopod opt-out data exists. Central falsifiable prediction: Sepia officinalis opt-out rate on difficult trials approximately 0.836 (bee baseline: 0.520). The prediction awaits experimental testing.