DRAS-5

Overview

Dynamic five-state risk assessment machine with constrained escalation and delayed de-escalation.

This repository is part of an eight-repository clinical decision-support research portfolio. Current status: manuscript or component package in preparation. The repository role is manuscript and supplementary.

Standard Repository Layout

Path	Purpose
src/	Package source code: dras5
tests/	Unit, smoke, and behavior checks
scripts/	Reproducibility and export scripts
examples/	Runnable examples and demonstrations
figures/, visualizations/, outputs/, results/	Generated visual and result artifacts
data/, models/, evaluation/	Dataset, model, and evaluation assets when used by this repo
FIGURE_MANIFEST.csv	Curated figure inventory for manuscript or component evidence
pyproject.toml, setup.py, requirements.txt, pytest.ini	Python package and test configuration

Architecture Flow

flowchart LR
    A[Input data or scenario] --> B[Core package logic]
    B --> C[Safety and quality checks]
    C --> D[Metrics and audit outputs]
    D --> E[Curated figures and result artifacts]

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Core Logic

• Map risk score to acuity state.
• Enforce monotonic escalation constraints.
• Apply C4 approval and C5 cooling-period rules.
• Export audit trail and simulation summaries.

Key Formulas And Rules

• Effective risk: R_eff(t) = R_current + (R_peak - R_current) * exp(-lambda * delta_t)
• Monotonic safety: S(t+1) >= S(t) unless C5 de-escalation constraints hold
• C4 approval: de-escalate only if approval=true and sustained low risk

Data, Results, Charts, And Graphs

The curated visual set is controlled by FIGURE_MANIFEST.csv and currently lists 6 figure entries. The manifest links figure IDs, roles, source scripts, source data, captions, sections, timestamps, and export DPI.

ID	Role	PNG	PDF
DRAS5-F1	manuscript	figures\fig1_state_machine.png	figures\fig1_state_machine.pdf
DRAS5-F2	manuscript	figures\fig2_pipeline.png	figures\fig2_pipeline.pdf
DRAS5-F3	manuscript	figures\fig6_sensitivity.png	figures\fig6_sensitivity.pdf
DRAS5-F4	manuscript	figures\fig10_performance.png	figures\fig10_performance.pdf

Reproduce

cd D:\PhD-NU\Manuscript\GitHub\DRAS-5
python -m venv .venv
.\.venv\Scripts\Activate.ps1
pip install -e .
python -m pytest -q

If figure-generation scripts are present, run the matching script listed in FIGURE_MANIFEST.csv from the repository root.

Verification Criteria

• Root metadata and package files are present.
• Source paths follow src/<package>/... where the package shape allows it.
• Tests pass with python -m pytest -q.
• Curated figures are listed in FIGURE_MANIFEST.csv rather than inferred from every raw image file.
• Manuscript status wording stays conservative: in preparation, implementation, supplementary, or reproducibility/component evidence as appropriate.
• No local manuscript path, external assistant wording, or software metadata block is kept in the repository text.

Portfolio Relationship

Repository	Role
BASICS-CDSS	Beyond-accuracy evaluation methodology
TRI-X	Framework-level package
ORASR	Routing and safety-action component
DRAS-5	Dynamic risk-state component
SAFE-Gate	Safety-gated ensemble framework
SynDX	Synthetic validation and explainability evidence
SURgul	SRGL/governance reproducibility component
TRI-X-CDSS	Integration and implementation package

Contact

Chatchai Tritham
Department of Computer Science and Information Technology, Faculty of Science, Naresuan University, Phitsanulok 65000, Thailand
Email: chatchait66@nu.ac.th
ORCID: 0000-0001-7899-228X

Chakkrit Snae Namahoot
Department of Computer Science and Information Technology, Faculty of Science, Naresuan University, Phitsanulok 65000, Thailand
Email: chakkrits@nu.ac.th
ORCID: 0000-0003-4660-4590