Cognitive Systems Engineering III: The Instrument & The Science

Technical Architecture, Empirical Calibration, and Falsification Methodology

The Engineering Discipline

Cognitive Systems Engineering (CSE) is an established engineering discipline originating at Ohio State University in 1982, founded in the aftermath of the Three Mile Island nuclear accident by David Woods and Erik Hollnagel. It studies how human operators and leadership teams make decisions under extreme load inside complex, high-consequence systems—such as nuclear power plants, aviation, military command, and critical care.

CSE III designates mastery-tier independent practice: auditing how human decision-making interacts with capital and operational architecture under conditions where failure is immediate and irreversible.

The Institutional Application

The instruments below apply cognitive systems engineering to a blind spot no conventional legal, financial, or AI audit addresses: reading the true structural condition of enterprises, credit structures, and leadership teams directly from raw operational telemetry—bypassing self-report, management spin, and consensus forecasts.

Two deterministic engines operate independently. Either can be deployed alone, or together to evaluate physical capital structures and human leadership resilience simultaneously.

1. Nova Verification Engine: Technical Architecture

The Nova Verification Engine is a rules-based, non-parametric computational gating harness. It ingests raw operational and financial data (SEC filings, binding debt covenants, cash-conversion ledgers, and throughput metrics), strips out management narrative at intake, and outputs a binary survival state.

Governing Architecture: Built on 33 first-principle structural boundary laws—each individually DOI-registered—and calibrated against more than 400 empirical failure conditions.
7-Stage Deterministic Pipeline: Zero probabilistic weighting, zero LLM guesswork, and zero manual overrides. The exact same filing fed into Nova on any day produces the exact same output.
Binary Output Identity: STATE 1 (Cleared) or STATE 0 (Rejected). No qualitative "watch lists," no blended risk scores, and no ambiguous middle ground.
Three Operational Channels:
- Predictive Channel: Pre-commitment clearance before capital moves or contracts are signed.
- Forensic Channel: Cold post-failure attribution from anonymized historical records.
- Falsification Channel: Continuous stress-testing of the 33 structural laws against live market data.
Public Record Validation: Validated across eight SEC EDGAR case studies (six historical collapses/recoveries and two active systemic alerts). Bidirectionally proven—rejecting WeWork at a $47B valuation while clearing Tesla in August 2018 when Wall Street consensus priced in bankruptcy.

2. Psychosocial Pressure Index (PPI): Technical Architecture

The Psychosocial Pressure Index (PPI) is a multi-dimensional temporal model of collective human cognition. While Nova audits balance sheets and operational telemetry, the PPI measures phase transitions in human leadership and collective decision-making under escalating load.

Empirical Scale: Calibrated across 22 million records, 28 data streams, and 406 measurement points inside a 70,000-line diagnostic codebase.
Multi-Modal Telemetry: Integrates operational communication lag with four-channel biometric and behavioral markers (EEG, HRV, facial affect, and voice prosody) where authorized.
Three-Tier Reality Gap Model: Tracks divergence across T1 (Objective Operational Reality), T2 (Mediated Reporting), and T3 (Executive Perceived Reality)—quantifying the exact gap between what is actually happening inside an organization and what leadership believes is happening.
Four-Phase State Classification: Maps organizational and market strain across four distinct mathematical regimes: LINEAR → NONLINEAR → RECURSIVE → COLLAPSE.
Core Control Parameters: Tracks the η coordination threshold (0.80), cognitive gating (SAG), feedback gain, and real-time collapse probability.

Cross-Market Portability: Six International Crisis Backtests

Applying the exact same phase-transition mathematics across five countries, six distinct crisis structures, and three decades:

2008 U.S. Financial Crisis: PPI detected COLLAPSE regime in March 2008 — 6 months prior to the Lehman Brothers bankruptcy (Sept 15, 2008).
2020 COVID Market Break: PPI detected COLLAPSE regime on March 13, 2020 — 10 days prior to the global equity market bottom (March 23, 2020).
2022 UK Gilt Crisis: PPI detected COLLAPSE regime on Sept 23, 2022 — 5 days prior to the Bank of England emergency intervention (Sept 28, 2022).
2015 Greek Sovereign Debt Crisis: PPI detected COLLAPSE regime on June 12, 2015 — 16 days prior to national capital controls (June 28, 2015).
1998 Russian Sovereign Default: PPI detected COLLAPSE regime on May 15, 1998 — 94 days prior to sovereign default (Aug 17, 1998).
1997 Thailand Baht Crisis: PPI detected COLLAPSE regime at the currency float — capturing regional contagion onset across July–Dec 1997.

Transparent Prediction Audit: Confirmations & Falsifications

Unlike black-box AI vendors that hide model misses, we publish both confirmed detections and falsified predictions alongside their exact mechanical root causes:

Live Verification Scorecard: 14 of 23 prospective detections confirmed (61%); 9 falsified (39%).
Root-Cause Attribution of Misses: All 9 falsified calls traced to a single parameter behavior—cognitive gating (SAG) absorbed the shock load rather than rebounding into a cascade.
Precision Timing Benchmark: In live prospective testing, the η coordination threshold crossing was isolated 33 days in advance down to a specific 3-day window (Jan 18–20, 2026).

Falsification Methodology & Scientific Provenance

Every law in our verification architecture is derived from first principles—never curve-fitted to historical market data—and governed by 423 explicit falsification conditions across the 33 structural laws, specifying the exact empirical thresholds that would disprove the model.

Permanent Open-Science Archives: Full theoretical derivations, mathematical constants, and falsification protocols are permanently archived with DOI continuity on OSF (DOI: 10.17605/OSF.IO/MVYZT), Zenodo, and ResearchGate.
Author & Persistent Identifiers: Don L. Gaconnet · ORCID: 0009-0001-6174-8384 · ISNI: 0000 0005 3079 9308 · SSRN Author ID: 7657314 (38 approved papers; ranked in the top 3% of global authors on SSRN).
Published Reference Volumes: Collapse Harmonics Codex I (ISBN: 9798282662177) and Codex II (ISBN: 9798992940831).
Cross-Domain Structural Correspondence: The mathematical boundary-rewriting behaviors formalized in our recursive topology laws exhibit direct structural correspondence with independent empirical findings published in Physics Letters B (Kolar et al., Vol. 871, 2025; CMS Collaboration, Vol. 874, 2026).

Challenge the Instrument on a Closed Case File

No pitch decks. No discovery calls. Submit an anonymized historical file from a closed, failed acquisition or defaulted credit facility—if Nova reconstructs the exact failure mechanics cold, we discuss live verification.