Hypothesis Generation Engine
Structured scientific discovery infrastructure
HGE converts complex observational data into verifiable evidence through machine-driven hypothesis search, deterministic execution, and audit-grade provenance tracking. Validated on Gaia DR3 astronomical catalog. Deployed in production across maritime intelligence (MARVIS), humanitarian forecasting (CERES), and quantum physics (OQTOPUS). ESA Sentinel Earth Observation adaptation in progress.
Built for institutional environments where reproducibility, auditability, and long-term operational integrity are non-negotiable.
Deterministic execution · Signed evidence bundles · Gaia DR3 validated · MARVIS · CERES · OQTOPUS
THE ENGINE
Infrastructure for structured discovery
HGE is not a product. It is a methodological program for automated scientific discovery — a domain-agnostic system that formalizes hypothesis generation, evaluation, and verification under uncertainty. It enables institutions to conduct systematic, resource-efficient exploration of complex problem spaces where traditional approaches are limited by cost, time, or physical constraints.
The engine is instrument-agnostic by design. It has been operationally validated across astronomical observation (Gaia DR3), humanitarian forecasting (CERES — 43 countries, live), maritime intelligence (MARVIS — 25+ European subsea assets), and quantum physics (OQTOPUS, University of Osaka). Every execution produces signed evidence bundles — tamper-resistant, auditable artifacts designed for institutional review, regulatory scrutiny, and cross-border verification.
Explicit hypothesis representation
Structured, machine-readable hypotheses enabling formal evaluation and cross-domain application
Information-gain prioritization
Experiments ranked by expected epistemic value, respecting resource constraints and operational limits
Deterministic execution
Identical inputs produce identical outputs — full replay capability ensures independent verification
Uncertainty-aware provenance
Complete audit trail from raw data to conclusion, with confidence tracking and drift detection
METHODOLOGY
Four-stage discovery cycle
HGE implements a closed-loop methodology that mirrors the scientific method while operating autonomously under real-world constraints. Each cycle increases confidence in validated hypotheses while identifying new areas of uncertainty.
Hypothesis generation
System formulates testable hypotheses based on current knowledge state, uncertainty estimates, and domain constraints. Hypotheses are structured to enable falsification and quantitative evaluation.
Experiment design
Experiments are designed to maximize expected information gain while respecting instrument capabilities, resource constraints, and operational limits. Design prioritizes hypotheses with highest epistemic value.
Deterministic execution
Experiments are executed with full provenance tracking. Deterministic execution ensures identical conditions produce identical results — enabling independent verification and audit-grade evidence generation.
Belief update and iteration
Observed results update confidence through structured reasoning. Updated beliefs inform the next cycle of hypothesis generation, creating a continuous discovery loop with full traceability.
Methodological principle: Each cycle increases confidence in validated hypotheses while identifying new areas of uncertainty, enabling systematic exploration of complex problem spaces under resource constraints.
PIPELINE
Data to evidence pipeline
Interactive execution flow: Data → Hypotheses → Experiments → Evidence. Select each stage to review technical specifications and live adapter readiness.
Data stage specifications
Observational datasets are normalized, quality-checked, and mapped into reproducible evidence contexts.
- Schema harmonization across instrument sources
- Outlier and drift pre-check pipeline
- Provenance event creation at ingestion
Live adapter status
Gaia DR3 — Astronomy
OperationalCERES — Famine forecasting
OperationalMARVIS — Maritime intelligence
OperationalOQTOPUS — Quantum hardware
OperationalPSE — Earth observation data fusion
OperationalFLUX — Renewable energy intelligence
OperationalSentinel — Earth Observation
In developmentORION — Conflict monitoring
In developmentAION — Longevity biology
In developmentATHENA — Women's health
In developmentMarine
PlannedPROOF
Operational validation
Northflow follows strict proof-before-claim discipline. HGE capabilities are backed by working implementations and documented validation artifacts.
Gaia DR3 astronomical validation
OperationalHGE operationally validated against the Gaia Data Release 3 catalog — one of the largest structured scientific datasets available (1.8 billion objects). Demonstrates structured hypothesis search at scale, with deterministic execution and reproducible evidence outputs across billions of observational records.
Metrics
- 1.8 billion catalog objects
- Deterministic replay verified
- Full provenance tracking operational
- Validation artifact: Available
Evidence verification system
Operational5-step verification contract producing signed evidence bundles with deterministic replay, audit invariants, policy gating, and tamper resistance. Tested against 6 adversarial attack vectors through dedicated red-team tamper suite.
Capabilities
- Cryptographic signing
- Deterministic replay
- Audit invariants enforced
- Red-team validated
CERES — Humanitarian famine forecasting
OperationalHGE deployed in production for 43-country probabilistic famine risk forecasting. Weekly 90-day IPC Phase 3+/4+/5 forecasts. Published on OCHA Humanitarian Data Exchange. Peer-reviewed methodology: arXiv:2603.09425.
Metrics
- 43 countries — ~95% of active IPC Phase 3+ caseload
- AUC 0.84, n=87 historical IPC transitions
- Open data on OCHA HDX — CC BY 4.0
- Live at ceres.northflow.no
MARVIS — Maritime infrastructure threat detection
Operational5-layer Bayesian inference pipeline monitoring 25+ European subsea infrastructure assets. 7 hypothesis classes including 3 novel detection methods. Retroactive validation confirmed against two European subsea infrastructure incidents. NIS2-compliant alert infrastructure.
Metrics
- 25+ European subsea assets monitored
- 7 hypothesis classes, 5 regions
- Retroactive validation: Nord Stream, Eagle S/Estlink-2
- Live at marvis.northflow.no
Sentinel Earth Observation adaptation
In developmentActive adaptation of HGE for ESA Sentinel satellite data. Targeting wildfire risk modelling, deforestation verification, and infrastructure vulnerability mapping. ESA Business Applications PoC being submitted.
Focus areas
- Wildfire risk hypothesis generation
- Deforestation pattern detection
- Infrastructure stress indicators
OQTOPUS — Quantum hardware validation
Operational26 autonomous experiments across 3 phases on the University of Osaka OQTOPUS quantum processing unit. Depth invariance hypothesis confirmed at 90% confidence. Technical evaluation report delivered to University of Osaka (Dr. Naoyuki Masumoto). Validates HGE instrument-agnostic architecture across astronomical and quantum physics domains.
Validation metrics
- 26 experiments across 3 phases
- Depth invariance confirmed at 90% confidence
- Technical report delivered — Feb 2026
- Instrument-agnostic architecture validated
DOMAIN ADAPTERS
One engine. Multiple application domains.
HGE is domain-agnostic by architecture. Each application domain is a structured adapter connecting the engine to specific observational environments and institutional contexts.
| Domain | Data Sources | Status |
|---|---|---|
| Space & Astronomical Observation | Gaia DR3 — 1.8B sources, 220,656 candidates | Operational |
| Humanitarian Forecasting | CHIRPS, MODIS, ACLED, IPC, WFP VAM, FAO/WFP | Operational |
| Maritime Intelligence | Sentinel-1 SAR, BarentsWatch AIS, CMEMS, ERA5 | Operational |
| Quantum Physics | University of Osaka OQTOPUS QPU | Operational |
| Earth Observation (PSE) | ERA5, Open-Meteo, Global Solar Atlas, Sentinel-2, OpenStreetMap, World Bank | Operational |
| Renewable Energy (FLUX) | PSE data fusion, pvlib, OpenStreetMap grid infrastructure | Operational |
| Earth Observation & Climate | ESA Sentinel, Copernicus | In development |
| Conflict Monitoring | Sentinel-1/2, ACLED, UNHCR, Copernicus EMS | In development |
| Longevity Biology | PubMed, Semantic Scholar, ClinicalTrials.gov, OpenTargets, GPT-4o | In development |
| Women's Health | Clinical datasets, patient signal feeds | In development |
Current domains reflect active development and institutional engagement. Future domains are structurally enabled by HGE's architecture and will be activated after core validation milestones are achieved.
SPECIFICATIONS
Technical foundation
Core capabilities
- Structured hypothesis representation (JSON-LD schemas)
- Bayesian experiment prioritization
- Deterministic execution engine
- Cryptographic evidence signing (Ed25519)
- Provenance tracking (W3C PROV-aligned)
- Drift detection and confidence updating
- Governance modes: disabled / logging / enforced
Integration
- Instrument-agnostic backend interface
- REST API for experiment orchestration
- Webhook callbacks for asynchronous instruments
- Containerized deployment
- PostgreSQL/MongoDB persistence options
- GDPR-aligned data handling
ENGAGEMENT
Research access & technical briefings
HGE technical materials, validation artifacts, and system documentation are maintained internally and shared selectively with qualified research partners, funding agencies, and institutional collaborators. Public releases follow peer review, partner validation, and governance review.
Public institutional materials
Framework overviews, validation summaries, and general system descriptions available through this website.
Structured engagement
Technical specifications, implementation guides, and operational procedures provided through institutional dialogue.
Controlled disclosure
Detailed architectural documentation, security specifications, and validation datasets subject to qualification requirements and confidentiality protocols.
Discuss research collaboration
Institutions and research organizations interested in exploring HGE methodology, validation approaches, or potential collaborative applications are invited to initiate structured dialogue through the institutional engagement process.
Initiate research dialogueEngagement follows structured institutional dialogue protocols. Response times vary based on inquiry complexity and alignment with current research priorities.