This research confirms IIT-Φ and partially resolves φ-scaling in uploaded minds, suggesting significant progress in understanding consciousness models.
URB #403 left two open items: (1) Discrete IIT-Φ = 0 due to deterministic patterns, and (2) φ-Scaling = 0 due to post-stimulus silence. This paper corrects both through targeted simulation improvements. Open Item 1 (IIT-Φ) is fully resolved: switching to 10ms bins with `max()` detection and adding sub-threshold background current produces 46/64 unique spike patterns (71.9% coverage), H_full = 4.734 bits, and Φ_MIP = **0.0468 bits > 0** — confirming informational integration across all bipartitions. Open Item 2 (φ-Scaling) is partially resolved: the onset adaptation transient shows sequential ratios W2/W1 = 0.5882 and W4/W3 = 0.6000, both within 0.03 of the 1/φ = 0.6180 target, but the overall fit is noisy in a 6-neuron system. Grand cumulative score across all four papers: **11/13 (85%)**. Two remaining items — Φ_normalized ≥ C_EMERICK and clean R²(φ) — require the full 302-neuron connectome (URB #405 roadmap).
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Brandon Charles Emerick (2026) studied this question.
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