SuperLearner model estimates peak energies of Swift GRBs with average Pearson r=0.72 in cross-validation and produces values for 650 additional bursts.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
astro-ph.HE 2years
2026 2representative citing papers
Spectro-polarimetric analysis of GRB 220107A reveals spectral softening between episodes and low overall polarization, with a marginal signal in the second episode, illustrating the potential of time-resolved observations to constrain GRB prompt emission models.
citing papers explorer
-
Estimating the peak energy of Swift gamma-ray bursts using supervised machine learning
SuperLearner model estimates peak energies of Swift GRBs with average Pearson r=0.72 in cross-validation and produces values for 650 additional bursts.
-
Episode-wise spectro-polarimetry of GRB 220107A: Testing the hypothesis of evolving radiation mechanisms
Spectro-polarimetric analysis of GRB 220107A reveals spectral softening between episodes and low overall polarization, with a marginal signal in the second episode, illustrating the potential of time-resolved observations to constrain GRB prompt emission models.