README.md

metadata

title: Fdrsm 4 Threshold Engine
emoji: 📚
colorFrom: indigo
colorTo: gray
sdk: docker
pinned: false
license: apache-2.0

FDRSM-4 — Threshold Engine (Docker)

FDRSM-4 is the fourth space in the Family Digital Risk Stabilization Model (FDRSM) series.
It implements a threshold / decision-facing layer that turns the stability core into reproducible governance outputs.

This space is structural and analytical:

• No behavioral profiling
• No content moderation
• No surveillance tooling
  It is designed for research interpretation, policy discussion, and method reproducibility.

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Model core

The baseline risk dynamic is:

[ \dot{R}(t) = (\alpha D - \beta k)R(t) ]

From the same baseline, the engine computes:

• Rate: (\lambda = \alpha D - \beta k)
• Stability margin: (\Delta = \beta k - \alpha D)
• Normalized fragility:
  [ F = \frac{|\Delta|}{|\alpha D| + |\beta k| + \varepsilon} ]

Interpretation

• Stable regime: (\lambda < 0)
• Unstable regime: (\lambda > 0)
• Near-boundary: (|\lambda| \le \text{tol})

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What FDRSM-4 produces

Given (\alpha, \beta, D, k) (and tolerance settings), the Space outputs:

1. Regime classification: Stable / Near-boundary / Unstable
2. Fragility class: Low / Moderate / High
3. Stability map with boundary line (k = (\alpha/\beta)D)
4. Risk trajectory plot (R(t)) using transparent Euler integration
5. Decision-facing governance interpretation (posture + decision + risk note)
6. Clean PDF report (no overlapping text, high-resolution figures)

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Series context (5-part roadmap)

• FDRSM-1 — Baseline Stability Model
  Formal stability condition and core dynamics.

• FDRSM-2 — Sensitivity & Fragility (Short Note)
  Diagnostics near the stability boundary without changing the baseline equation.

• FDRSM-3 — Governance Scenario Lab
  Scenario interpretation layer: regime → governance posture.

• FDRSM-4 — Threshold Engine (this Space)
  Reproducible threshold logic + report generator.

• FDRSM-5 — Validation / Stress Tests (planned)
  Robustness checks, perturbation sweeps, and structured evaluation notebooks.

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Repository structure

• main.py — Gradio app entrypoint
• engine/thresholds.py — diagnostics + interpretation + simulation
• engine/regimes.py — regime + fragility classification
• engine/validation.py — strict input validation
• outputs/ — reserved for future exported artifacts

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How to use

1. Adjust parameters (\alpha, \beta, D, k)
2. Click Run Threshold Engine
3. Inspect:
   • trajectory plot
   • stability map
   • report text
4. Download the generated PDF report

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Author

Abdessamad Bourkibate
Independent Researcher — Family Cybersecurity & System Governance (Morocco)
ORCID: 0009-0000-6186-8071

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License

Apache-2.0
Rights holder line is displayed in the PDF footer only.