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<ri:Resource created="2022-07-19T08:33:14Z" status="active" updated="2025-05-19T09:50:00Z" version="1.2" xmlns:cs="http://www.ivoa.net/xml/ConeSearch/v1.0" xmlns:ri="http://www.ivoa.net/xml/RegistryInterface/v1.0" xmlns:vr="http://www.ivoa.net/xml/VOResource/v1.0" xmlns:vs="http://www.ivoa.net/xml/VODataService/v1.1" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.ivoa.net/xml/ConeSearch/v1.0 http://vo.ari.uni-heidelberg.de/docs/schemata/ConeSearch.xsd http://www.ivoa.net/xml/VOResource/v1.0 http://vo.ari.uni-heidelberg.de/docs/schemata/VOResource.xsd http://www.ivoa.net/xml/VODataService/v1.1 http://vo.ari.uni-heidelberg.de/docs/schemata/VODataService.xsd" xsi:type="vs:CatalogService"><title>Predicted redshifts for 4FGL gamma-ray loud AGNs</title><shortName>J/ApJS/259/55</shortName><identifier>ivo://CDS.VizieR/J/ApJS/259/55</identifier><altIdentifier>doi:10.26093/cds/vizier.22590055</altIdentifier><curation><publisher ivo-id="ivo://CDS">CDS</publisher><creator><name>Narendra A.</name></creator><creator><name>Gibson S.J.</name></creator><creator><name>Dainotti M.G.</name></creator><creator><name>Bogdan M.</name></creator><creator><name>Pollo A.</name></creator><creator><name>Liodakis I.,Poliszczuk A.</name></creator><creator><name>Rinaldi E.</name></creator><date role="Updated">2022-08-26T08:04:48Z</date><date role="Created">2022-07-19T08:33:14Z</date><contact><name>CDS support team</name><address>CDS, Observatoire de Strasbourg, 11 rue de l'Universite, F-67000 Strasbourg, France</address><email>cds-question@unistra.fr</email></contact></curation><content><subject>active-galactic-nuclei</subject><subject>gamma-ray-astronomy</subject><subject>astronomical-models</subject><subject>redshifted</subject><description>Measuring the redshift of active galactic nuclei (AGNs) requires the use of time-consuming and expensive spectroscopic analysis. However, obtaining redshift measurements of AGNs is crucial as it can enable AGN population studies, provide insight into the star formation rate, the luminosity function, and the density rate evolution. Hence, there is a requirement for alternative redshift measurement techniques. In this project, we aim to use the Fermi Gamma-ray Space Telescope's 4LAC Data Release 2 catalog to train a machine-learning (ML) model capable of predicting the redshift reliably. In addition, this project aims at improving and extending with the new 4LAC Catalog the predictive capabilities of the ML methodology published in Dainotti et al. Furthermore, we implement feature engineering to expand the parameter space and a bias correction technique to our final results. This study uses additional ML techniques inside the ensemble method, the SuperLearner, previously used in Dainotti et al. Additionally, we also test a novel ML model called Sorted L-One Penalized Estimation. Using these methods, we provide a catalog of estimated redshift values for those AGNs that do not have a spectroscopic redshift measurement. These estimates can serve as a redshift reference for the community to verify as updated Fermi catalogs are released with more redshift measurements.</description><source format="bibcode">2022ApJS..259...55N</source><referenceURL>https://cdsarc.cds.unistra.fr/viz-bin/cat/J/ApJS/259/55</referenceURL><type>Catalog</type><contentLevel>Research</contentLevel><relationship><relationshipType>IsServedBy</relationshipType><relatedResource ivo-id="ivo://CDS.VizieR/TAP">TAP VizieR generic service</relatedResource></relationship><relationship><relationshipType>IsServedBy</relationshipType><relatedResource>Conesearch service</relatedResource></relationship><relationship><relationshipType>related-to</relationshipType><relatedResource ivo-id="ivo://CDS.VizieR/IX/67">IX/67 : Incremental Fermi LAT 4th source cat. (4FGL-DR3) (Fermi-LAT col., 2022)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJ/690/1236">J/ApJ/690/1236 : COSMOS photometric redshift catalog (Ilbert+, 2009)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/A+A/523/A48">J/A+A/523/A48 : Gaia photometry (Jordi+, 2010)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJ/774/157">J/ApJ/774/157 : Swift GRBs with X-ray afterglows and z&lt;9.5 (Dainotti+, 2013)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/MNRAS/428/220">J/MNRAS/428/220 : Gamma-ray AGN type determination (Hassan+, 2013)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/MNRAS/437/968">J/MNRAS/437/968 : AGN automatic photometric classification (Cavuoti+, 2014)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJ/782/41">J/ApJ/782/41 : 231 AGN candidates from the 2FGL catalog (Doert+, 2014)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/MNRAS/462/3180">J/MNRAS/462/3180 : 3FGL Blazar of Unknown Type classification (Chiaro+, 2016)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/A+A/602/A86">J/A+A/602/A86 : Blazar cand. among Fermi/LAT 3FGL cat. (Lefaucheur+, 2017)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/AJ/154/269">J/AJ/154/269 : A new photo-z method for quasars in Stripe 82 (Yang+, 2017)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/A+A/619/A14">J/A+A/619/A14 : Classification-aided zph estimation (Fotopoulou+, 2018)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/A+A/611/A97">J/A+A/611/A97 : Phot. quasar candidates in Stripe 82 (Pasquet-Itam+, 2018)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJS/247/33">J/ApJS/247/33 : Fermi LAT fourth source catalog (4FGL) (Abdollahi+, 2020)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJ/892/105">J/ApJ/892/105 : 4th cat. of Fermi LAT-detected AGNs (4LAC) (Ajello+, 2020)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/A+A/633/A154">J/A+A/633/A154 : HDBSCAN star, galaxy, QSO classification (Logan+, 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