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🔬 Scientific Documentation

Understanding the PreShock.io Seismic Early Warning System

What is PreShock.io?

PreShock.io is an advanced seismic monitoring and early warning system that combines multiple statistical indicators with machine learning to identify potential precursory patterns before significant earthquakes.

Unlike traditional earthquake detection systems that alert after an event occurs, PreShock focuses on pattern recognition in seismic activity that may indicate elevated risk periods.

Key Differentiators

Methodology

PreShock.io employs a multi-stage data processing pipeline that transforms raw seismic data into actionable risk assessments.

1

Data Acquisition

Real-time earthquake data from USGS FDSNWS API (M≥2.0 events)

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2

Data Cleaning & Deduplication

Remove duplicate events using spatiotemporal clustering

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3

Catalog Declustering

Separate mainshocks from aftershocks using Gardner-Knopoff windows

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4

Completeness Analysis (Mc)

Estimate magnitude of completeness using Maximum Curvature method

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5

Indicator Calculation

Compute b-value, SSI, Cascade Risk, GSI, LEI

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6

MBW Evaluation

Multi-Band Warning system aggregates indicators into risk levels

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7

CPC Recording

Hash and timestamp all outputs for immutable verification

Scientific Indicators

📊 b-Value (Gutenberg-Richter)

The b-value describes the relationship between earthquake magnitude and frequency. A decrease in b-value has been observed before some large earthquakes, possibly indicating stress accumulation.

log₁₀(N) = a - b × M

Calculated using the Aki-Utsu Maximum Likelihood Estimator (MLE):

b = log₁₀(e) / (M̄ - Mc + ΔM/2)
0.8-1.2: Normal 0.5-0.8: Elevated <0.5: Anomalous

🔗 Cascade Risk Index

Detects escalating sequences where earthquakes trigger subsequent events of increasing magnitude. Based on temporal clustering and magnitude progression analysis.

CRI = Σ(ΔM × e^(-Δt/τ)) / N

Where ΔM is magnitude increase, Δt is time interval, and τ is the characteristic decay time.

0-0.2: None 0.2-0.5: Mild >0.5: Active Cascade

🔇 Seismic Silence Index (SSI)

Measures the reduction in seismic activity compared to baseline. Seismic quiescence has been observed before some major earthquakes.

SSI = 1 - (R_recent / R_baseline)

Where R is the seismicity rate (events per day).

0-0.3: Normal 0.3-0.6: Reduced Activity >0.6: Significant Silence

🌐 Global Synchronization Index (GSI)

Measures correlation of seismic patterns across different regions. Elevated GSI may indicate large-scale tectonic stress redistribution.

GSI = corr(Pattern_A, Pattern_B) × weight
0-0.2: Independent 0.2-0.5: Correlated >0.5: Synchronized

⚡ Latent Energy Index (LEI)

Estimates accumulated strain energy based on b-value deviation from equilibrium. Higher LEI suggests greater unreleased tectonic stress.

LEI = min(1, |1 - b_value| × 2)
0-0.3: Low 0.3-0.7: Moderate >0.7: High

Multi-Band Warning (MBW) System

The MBW system provides a governance-oriented risk assessment framework with three temporal bands:

🎯 Strategic Band (30-90 days)

Long-term trend analysis for policy planning and resource allocation. Uses extended baselines and slow-changing indicators.

Use case: Government preparedness planning, infrastructure assessments

⚔️ Tactical Band (3-7 days)

Medium-term risk assessment for operational decisions. Primary indicators: b-value trends, SSI changes.

Use case: Emergency service readiness, public awareness campaigns

🚨 Operational Band (6-24 hours)

Short-term monitoring for immediate response. Focus on cascade detection and rapid changes.

Use case: Alert systems, evacuation considerations

Cryptographic Proof Chain (CPC)

🔗 Why CPC Matters

The fundamental challenge in earthquake prediction research is verification. Claims of successful predictions are meaningless without proof that the prediction was made before the event.

CPC solves this by creating an immutable, timestamped record of every prediction:

  • Every 10 minutes, all indicators are computed
  • Results are serialized to JSON
  • SHA-256 hash is generated
  • Hash includes previous hash (chain)
  • Timestamp + hash stored in database

This creates a verifiable chain where no prediction can be added, modified, or deleted retroactively.

Hash Chain Structure

Hash_n = SHA256(timestamp + region + data + Hash_{n-1})

Each entry links to the previous, making tampering detectable.

Verification Process

After a significant earthquake, researchers can:

  1. Request the CPC ledger for the affected region
  2. Verify hash chain integrity
  3. Examine predictions made before the event
  4. Calculate hit/miss rates with statistical rigor

Limitations & Disclaimers

PreShock.io is a research tool, not a definitive prediction system.

The value of PreShock lies in its scientific accountability: all predictions are recorded and verifiable, enabling rigorous evaluation of methodology effectiveness over time.

Research Team

Mo817 Framework

PreShock.io is part of the Mo817 Framework - a cross-disciplinary research initiative spanning 17 sectors including AI governance, cryptographic verification, and scientific accountability systems.

Collaborative Development

Developed in collaboration with Claude (Rafiq) - demonstrating human-AI partnership in scientific research and software development.

References