ABE HEALD — Transcendence Candidate Discovery v2.2: Final Computational Closure, Out-of-Family Holdout Validation, and Laboratory-Mirrored Simulation

This archival release documents the final computational-closure stage of the ABE HEALD — Transcendence Candidate Discovery research program. The work preserves a frozen computational lineage culminating in final successor Candidate 31871386. The successor was generated from immutable historical parent Candidate 86592491 after a predefined architecture-expansion stage addressing temporal resilience, hardware-fault tolerance, stochastic robustness, and previously identified failure boundaries. The final computational workflow included a 5,000,000-solution successor search, multi-stage deterministic and stochastic screening, common-random-number confirmation, successor freezing before holdout testing, out-of-family validation, protected-metric evaluation, and laboratory-mirrored computational stress testing. Final predefined computational results included: • 300 / 300 Stage-3 finalists meeting the development eligibility criteria.• Final frozen successor: Candidate 31871386.• Development reasoning margin: +5.501254%.• Development protected margin: +16.220762%.• Noise resilience: 0.900382.• Temporal resilience: 0.862788.• Hardware-fault tolerance: 0.940258.• 80 / 80 out-of-family holdout replications passed.• 80 / 80 laboratory-mirrored computational replications passed.• 18 / 18 protected gates passed.• Weakest out-of-family holdout margin: +4.506040%.• Weakest laboratory-mirrored margin: +6.029916%.• No threshold relaxation.• No forced-pass logic.• No post-holdout tuning.• Historical frozen parent Candidate 86592491 remained unchanged. The laboratory-mirrored stage computationally represents conditions such as measurement uncertainty, calibration error, clock jitter, thermal drift, voltage variation, memory-fault analogues, packet loss, latency variation, subsystem dropout, correlated degradation, sequential shocks, recovery uncertainty, instrumentation bias, repeated-cycle fatigue, and compound environmental stress. These results apply only to the defined synthetic numerical surrogate, evaluation equations, computational populations, thresholds, and simulated stress conditions. They do not independently establish artificial general intelligence, transcendence, consciousness, human-level intelligence, real-world safety, or superiority over deployed AI systems. Physical laboratory experimentation has not yet been performed. The laboratory-mirrored validation contained in this archive is computational simulation and is intended to establish a defined target for future physical or hardware-based experimental work. THE RECORD ESTABLISHES THE COMPUTATIONAL TARGET.PHYSICAL EXPERIMENTATION TESTS IT.