Artificial Organism Intelligence v3.0 — QNIF, Molecular Topology Circuit Derivation, and Steroid-Tryptamine TE Bridges

Version 3.0 of the Artificial Organism Intelligence (AOI) framework, extending the original 8-subsystem bio-inspired adaptive computation architecture with five major innovations: 1. Quantum Neural-Immune Fusion (QNIF): A 5-layer bio-quantum synthesis architecture (Skin, Genome, Brain, Immune, Gate) that unifies all subsystems into a single pipeline processing environmental signals in under 2 seconds. 2. Molecular Topology to Quantum Circuit Derivation: A novel method for generating quantum circuit parameters (qubit count, shot count, gate count, channel count) directly from fused molecular graph topology. Demonstrated through stanozolol-DMT and testosterone-DMT conjugate products. 3. Stanozolol-DMT Transposable Edge Bridge: 11-ring processing pipeline, 13 decision gates, 16 qubits, 8192 shots, dual thermal regime controller (230C/250C). Precision/scalping signal profile. 4. Testosterone-DMT Transposable Edge Bridge: 4-ring pipeline, 4 strict gates (ALL must pass), 8 qubits, 4096 shots, novel aromatase controller implementing hormone-inspired aggressive-to-defensive regime switching. 5. Automated Evolutionary Training Pipeline: 1500-expert army generation via prop firm simulation, automated data collection, QNIF signal refresher (MT5-free), and hot-reload model deployment. All biological mechanisms grounded in peer-reviewed molecular biology. All systems implemented, tested, and operational. Builds on Version 2.0 (DOI: 10.5281/zenodo.18526575, published February 8, 2026). Erratum (2026-07-29): The QNIF molecular-topology circuit-parameter derivation described here fails the placement-invariance test on all three arms. Both theorems it states hold for 40,320 of 40,320 slot placements — they are bit-3 parity tautologies, true even for a circuit with no couplings — so they carry zero bits of information about the molecular topology. The shipped list-order placement scores 7/11 where degree-preserving random rewirings average 9.914 (p = 0.814), meaning the real molecular assignment does worse than scrambled placements given a smaller search budget. Nothing in the construction fixes which molecular feature occupies which circuit slot, which is the precondition the test targets. See 10.5281/zenodo.21684226. Annotation (2026-08-14): Superseded. This AOI v3.0/QNIF record is superseded by the verified AOI v4 record 10.5281/zenodo.21368154. Prefer that record for any operational claim.