  Scintillator detector response modelling has become an essential tool in
various research fields such as particle and nuclear physics, astronomy or
geophysics. Yet, due to the system complexity and the requirement for accurate
electron response measurements, model inference and calibration remains a
challenge. Here, we propose Compton edge probing to perform non-proportional
scintillation model (NPSM) inference for inorganic scintillators. We use
laboratory-based gamma-ray radiation measurements with a NaI(Tl) scintillator
to perform Bayesian inference on a NPSM. Further, we apply machine learning to
emulate the detector response obtained by Monte Carlo simulations. We show that
the proposed methodology successfully constrains the NPSM and hereby quantifies
the intrinsic resolution. Moreover, using the trained emulators, we can predict
the spectral Compton edge dynamics as a function of the parameterized
scintillation mechanisms. The presented framework offers a novel way to infer
NPSMs for any inorganic scintillator without the need for additional electron
response measurements.
