Catalogue of Bayesian SZNet's spectroscopic redshift predictions

The "dr16q_superset_redshift.csv" file provides a catalogue of spectroscopic redshift predictions for spectra from the 16th data release of the Sloan Digital Sky Survey (SDSS) quasar superset catalogue (Lyke et al., 2020). Redshifts are predicted by a Bayesian convolutional neural network named Bayesian SZNet with associated predictive uncertainties in the form of predictive variances. The catalogue is released in the CSV format with the following columns: <em>plate</em>: spectroscopic plate number; <em>mjd</em>: modified Julian day of the spectroscopic observation; <em>fiberid</em>: fiber identification number; <em>z_pred</em>: redshift from Bayesian SZNet; <em>variance</em>: predictive variance associated with redshift from Bayesian SZNet; <em>z</em>: primary redshift; <em>source</em><em>_z</em>: origin of the reported redshift in <em>z;</em> <em>is_qso_final</em>: flag indicating quasars included in the DR16Q (Lyke et al., 2020); <em>z_vi</em>: redshift from visual inspection; <em>z_pipe</em>: redshift from the SDSS pipeline; <em>zwarning</em>: quality flag on the redshift from the SDSS pipeline; <em>z_dr12q</em>: redshift from the DR12Q catalogue (Pâris et al., 2017); <em>z_dr7q_sch</em>: redshift from the DR7Q catalogue (Schneider et al., 2010); <em>z_dr6q_hw</em>: redshift from the DR6 catalogue (Hewett and Wild, 2010); <em>z_10k</em>: redshift from the random visual inspection of 10000 spectra in the DR16Q superset; <em>z_pca</em>: redshift from the redvsblue algorithm; <em>z_qn</em>: redshift from QuasarNET (Busca and Balland, 2018); <em>z_pred_1</em> to <em>z_pred_256</em>: sampled redshifts from Bayesian SZNet; where columns <em>z</em>, <em>source_z</em>, <em>is_qso_final</em>, <em>z_vi</em>, <em>z_pipe</em>, <em>zwarning</em>, <em>z_dr12q</em>, <em>z_dr7q_sch</em>, <em>z_dr6q_hw</em>, <em>z_10k</em>, <em>z_pca</em>, and <em>z_qn</em> are taken from the 16th data release of the SDSS quasar superset catalogue.