Catalogue of Bayesian SZNet's spectroscopic redshift predictions
<p>The "dr16q_superset_redshift.csv" file provides a catalogue of spectroscopic redshift predictions for spectra from the <a href="https://www.sdss.org/dr16/algorithms/qso_catalog/">16th data release of the Sloan Digital Sky Survey (SDSS) quasar superset catalogue</a> <a href="https://ui.adsabs.harvard.edu/abs/2020ApJS..250....8L/abstract">(Lyke et al., 2020)</a>. 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:</p> <ul> <li><em>plate</em>: spectroscopic plate number;</li> <li><em>mjd</em>: modified Julian day of the spectroscopic observation;</li> <li><em>fiberid</em>: fiber identification number;</li> <li><em>z_pred</em>: redshift from Bayesian SZNet;</li> <li><em>variance</em>: predictive variance associated with redshift from Bayesian SZNet;</li> <li><em>z</em>: primary redshift;</li> <li><em>source</em><em>_z</em>: origin of the reported redshift in <em>z;</em></li> <li><em>is_qso_final</em>: flag indicating quasars included in the DR16Q <a href="https://ui.adsabs.harvard.edu/abs/2020ApJS..250....8L/abstract">(Lyke et al., 2020)</a>;</li> <li><em>z_vi</em>: redshift from visual inspection;</li> <li><em>z_pipe</em>: redshift from the SDSS pipeline;</li> <li><em>zwarning</em>: quality flag on the redshift from the SDSS pipeline;</li> <li><em>z_dr12q</em>: redshift from the DR12Q catalogue <a href="http://ui.adsabs.harvard.edu/abs/2017A%26A...597A..79P/abstract">(Pâris et al., 2017)</a>;</li> <li><em>z_dr7q_sch</em>: redshift from the DR7Q catalogue <a href="https://ui.adsabs.harvard.edu/abs/2010AJ....139.2360S/abstract">(Schneider et al., 2010)</a>;</li> <li><em>z_dr6q_hw</em>: redshift from the DR6 catalogue <a href="https://ui.adsabs.harvard.edu/abs/2010MNRAS.405.2302H/abstract">(Hewett and Wild, 2010)</a>;</li> <li><em>z_10k</em>: redshift from the random visual inspection of 10000 spectra in the DR16Q superset;</li> <li><em>z_pca</em>: redshift from the <a href="https://ascl.net/2106.017">redvsblue algorithm</a>;</li> <li><em>z_qn</em>: redshift from QuasarNET <a href="https://arxiv.org/abs/1808.09955">(Busca and Balland, 2018)</a>;</li> <li><em>z_pred_1</em> to <em>z_pred_256</em>: sampled redshifts from Bayesian SZNet;</li> </ul> <p>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.</p>
ShareScore
44/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 8
- Access
- 20
- Reuse readiness
- 8
- Engagement
- 4