ModelMOD-2026-0005v0.1

Bayesian reference (exact posterior / Beta-Bernoulli / joint common-cause / HMM)

The probabilistic side of every comparison: exact posteriors with numerical reliabilities, Beta-Bernoulli source-quality learning, the joint-likelihood common-cause model for correlated clusters (and its naive-independence negative control), and a Bayesian HMM for regime switches.

Research status

STABLE the current conclusions are relatively stable

Evidence level

E2 Controlled experiment

Data basis

SYNTHETIC Synthetic data and theoretical reasoning. Many now treat synthetic data as if it were real; this laboratory says the opposite deliberately — until a real hybrid model exists, an inference is only an inference, and theoretically possible is not actually possible.

Version

0.1

Updated

2026-09-09

Created

2026-09-08

Domain

Model Representation

Program

PRG-2026-0001 Adaptive Epistemic Systems

Authors

Neo.K (EveMissLab)

AI collaborators

Sol (GPT-5.6, OpenAI ChatGPT)