JOR Framework PyMC v1.0

Initial stable release of the PyMC implementation of the James Orion Report (JOR) Framework.

This release enables Bayesian posterior estimation for SOP and NHP values generated under JOR Framework v3.

Included in this release:

• jor_fusion.py – generates SOP/NHP case scores
• jor_pymc.py – PyMC Bayesian model
• jor_pymc_runner.py – performs posterior analysis
• Example datasets and output distributions

Purpose:
Provide a reproducible Bayesian workflow for structured UAP case analysis.

Notes:
NHP is conditionally dependent on SOP according to JOR Framework logic.

Citation:
If you use this software, please cite the Zenodo dataset:

James Orion Report (JOR) Framework PyMC Dataset
DOI: 10.5281/zenodo.18157347