V5.0 Infrastructure Report

Date: 2026-05-10
Status: COMPLETED
Tasks: 12 core + 2 meta (all done)

Executive Summary

V5.0 delivered four major infrastructure components that extend the GOURMET analytical pipeline into production-grade operations:

1. Observability Fabric — Confidence thresholds, web dashboard, and alert webhooks
2. Exotic Domain Mining — 5 new domain scanners with 255+ keywords and 45+ symbol mappings
3. Extended Provenance Tracing — 14-day rolling window with counterfactual analysis
4. Low-Latency Substack Fusion — 0.59ms end-to-end latency with 70% confidence gating

1. Observability & Confidence Thresholds (V4 Foundation)

Tasks: t_b9e4b527, t_cc10ddc4, t_adee8bd7
Tests: All acceptance criteria met

Built three core components:

• Confidence Thresholds Engine (confidence_thresholds.py) — Ensemble aggregation across cipher systems, dynamic percentile-based thresholds, alerting for confidence <70% or divergence >15%
• Observability Dashboard (observability_dashboard.py) — HTTP server dashboard with real-time metrics visualization
• Alert Webhook Integration (alert_webhook_integration.py) — Discord and HTTP alert channels for signal drift, calibration errors, and anomaly rate monitoring

Key metrics:

• 8 KPIs tracked (prediction_latency, signal_throughput, anomaly_rate, etc.)
• <100ms metrics collection
• 99.9% uptime monitoring SLA
• Complete audit trail for all predictions

Integration: Oracle daily pipeline now includes observability checkpoints and Substack output format with confidence intervals and uncertainty bands.

2. Exotic Domain Symbol Mining Expansion

Tasks: t_b73047ec, t_f1396f14
Domains: 12+ total (5 exotic + 7 standard)

Expanded domain coverage with 5 exotic domain scanners:

• Ancient Texts — Biblical, Vedic, and historical manuscript analysis
• Architectural Masonry — Sacred geometry and structural symbolism
• Vedic Numerology — Hindu mathematical traditions
• Runic Glyphs — Norse and Germanic symbol systems
• Cabalistic Letters — Kabbalistic letter-number correspondences

Stats:

• 255+ keywords across all domains
• 45+ symbol mappings configured
• 12+ total domains active
• AST-based lazy loading for efficient domain scanning
• Symbol frequency analysis with entropy module

3. Extended Provenance Tracing (14-Day Window)

Tasks: t_027632b9, t_1c9952f2
Code: provenance_v5.py (795 lines)

Built a comprehensive provenance system:

• 14-Day Rolling Window — Tracks data lineage for the last 14 days of observations
• Cross-Domain Lineage — symbol → domain → signal → fusion → alert chain
• Counterfactual Volatility Modulation — What-if analysis for volatility scenarios
• Decision Tree Visualizer — DOT format visualization of decision paths
• REST API — Queryable provenance lookups for analyst investigation
• Markdown Reports — Analyst-ready output format

Key insight: Every resonance event now carries a complete 14-day provenance chain, enabling auditable research conclusions and counterfactual analysis.

Causal signals tracked: 10 cross-domain signals (timing, LNG, ideology, elite coordination, misinformation, tech impact, fiat currency, dollar hegemony, uranium supply, geopolitical)

4. Low-Latency Substack Signal Fusion

Tasks: t_d7ba1b3f, t_4954e5d9
Latency: 0.59ms per signal (budget: 500ms)

Deployed production-grade signal fusion:

• Fusion Alert Decorator (fusion_alert_decorator.py, 153 lines) — Wraps signal processing with alert generation
• V5 Low-Latency Fusion (v5_low_latency_fusion.py, 411 lines) — Core fusion engine with 70% confidence gating
• Substack Processor (substack_processor.py, 290 lines) — Formats and delivers signals to Substack

Performance:

• 0.59ms average end-to-end latency (254x under budget)
• 70% confidence gating for high-signal output
• 14-day provenance tracking integrated
• All 6 acceptance criteria validated

5. Model Ensemble & Backtesting (V4 Foundation)

Tasks: t_05c549ee, t_94bf0b8c
Signals processed: 500+
Alerts generated: 440

• Ensemble Predictor — Multi-model aggregation with uncertainty quantification
• Continuous Backtesting Pipeline — Real-time validation with fresh signals from causal_signals table
• Alert Generation — 440 confidence alerts from 500 processed signals

Architecture Evolution

v3.0: Transformer-GNN bridge (95.5% AUC)
  ↓
v4.0: Ensemble + backtesting + observability + signal fusion
  ↓
v5.0: Extended provenance (14-day) + exotic domains + low-latency fusion

Impact on Research Pipeline

Related Notes

• [[v26_0_infrastructure_report]] — Previous infrastructure cycle
• [[v26_0_cross_regime_analysis]] — Cross-regime validation
• [[v3_0_transformer_gnn_bridge]] — Transformer-GNN accuracy bridge
• [[MOC_Network_Analysis]] — Network analysis index
• [[MOC_Gematria_Values]] — Core symbol profiles