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<ri:Resource created="2019-09-03T14:40:51Z" 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>Automated triage and vetting of TESS candidates</title><shortName>J/AJ/158/25</shortName><identifier>ivo://CDS.VizieR/J/AJ/158/25</identifier><altIdentifier>doi:10.26093/cds/vizier.51580025</altIdentifier><curation><publisher ivo-id="ivo://CDS">CDS</publisher><creator><name>Yu L.</name></creator><creator><name>Vanderburg A.</name></creator><creator><name>Huang C.</name></creator><creator><name>Shallue C.J.</name></creator><creator><name>Crossfield I.J.M.,Gaudi B.S.</name></creator><creator><name>Daylan T.</name></creator><creator><name>Dattilo A.</name></creator><creator><name>Armstrong D.J.</name></creator><creator><name>Ricker G.R.,Vanderspek R.K.</name></creator><creator><name>Latham D.W.</name></creator><creator><name>Seager S.</name></creator><creator><name>Dittmann J.</name></creator><creator><name>Doty J.P.,Glidden A.</name></creator><creator><name>Quinn S.N.</name></creator><date role="Updated">2020-12-23T07:27:46Z</date><date role="Created">2019-09-03T14:40:51Z</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>multiple-stars</subject><subject>exoplanets</subject><subject>apparent-magnitude</subject><subject>astronomical-models</subject><description>NASA's Transiting Exoplanet Survey Satellite (TESS) presents us with an unprecedented volume of space-based photometric observations that must be analyzed in an efficient and unbiased manner. With at least ~1000000 new light curves generated every month from full-frame images alone, automated planet candidate identification has become an attractive alternative to human vetting. Here we present a deep learning model capable of performing triage and vetting on TESS candidates. Our model is modified from an existing neural network designed to automatically classify Kepler candidates, and is the first neural network to be trained and tested on real TESS data. In triage mode, our model can distinguish transit-like signals (planet candidates and eclipsing binaries) from stellar variability and instrumental noise with an average precision (the weighted mean of precisions over all classification thresholds) of 97.0% and an accuracy of 97.4%. In vetting mode, the model is trained to identify only planet candidates with the help of newly added scientific domain knowledge, and achieves an average precision of 69.3% and an accuracy of 97.8%. We apply our model on new data from Sector 6, and present 288 new signals that received the highest scores in triage and vetting and were also identified as planet candidates by human vetters. We also provide a homogeneously classified set of TESS candidates suitable for future training.</description><source format="bibcode">2019AJ....158...25Y</source><referenceURL>https://cdsarc.cds.unistra.fr/viz-bin/cat/J/AJ/158/25</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/IV/38">IV/38 : TESS Input Catalog - v8.0 (TIC-8) (Stassun+, 2019)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJ/809/77">J/ApJ/809/77 : Transiting Exoplanet Survey Satellite (TESS) (Sullivan+, 2015)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/AJ/156/102">J/AJ/156/102 : TESS Input Catalog and Candidate Target List (Stassun+, 2018)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJS/239/2">J/ApJS/239/2 : Simulated exoplanets from TESS list of targets (Barclay+, 2018)</relatedResource></relationship></content><rights>https://cds.unistra.fr/vizier-org/licences_vizier.html</rights><capability><interface xsi:type="vr:WebBrowser"><accessURL use="full">https://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/AJ/158/25</accessURL><mirrorURL title="VizieR at IUCAA: Pune, India">https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/AJ/158/25</mirrorURL><mirrorURL title="VizieR at SAAO: SAAO, South Africa">http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/AJ/158/25</mirrorURL></interface></capability><capability><interface xsi:type="vs:ParamHTTP"><accessURL use="base">https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/AJ/158/25</accessURL><mirrorURL title="VizieR at IUCAA: Pune, 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Should Not be used for identification.</description><ucd>meta.record</ucd><dataType xsi:type="vs:VOTableType">int</dataType></column><column><name>TIC</name><description>[4616346/10001673159] TESS Input Catalog identifier</description><ucd>meta.id;meta.main</ucd></column><column><name>Tmag</name><description>[6.781/11.995] TESS-band magnitude</description><unit>mag</unit><ucd>phot.mag;em.opt</ucd><dataType xsi:type="vs:VOTableType">float</dataType></column><column><name>Per</name><description>[0.259746/13.9862] Period</description><unit>d</unit><ucd>time.period</ucd><dataType xsi:type="vs:VOTableType">double</dataType></column><column><name>T0</name><description>[1325.7/1481.82] Epoch of transit (BJD_TDB_-2457000)</description><unit>d</unit><ucd>time.epoch</ucd><dataType xsi:type="vs:VOTableType">double</dataType></column><column><name>Dur</name><description>[0.74/11.43] Transit duration</description><unit>h</unit><ucd>time.duration</ucd><dataType xsi:type="vs:VOTableType">float</dataType></column><column><name>Depth</name><description>[190/38350] Transit depth</description><unit>(10-6)</unit><ucd>phys.absorption.opticalDepth</ucd><dataType xsi:type="vs:VOTableType">int</dataType></column><column><name>Tri</name><description>[0.164/0.998] Triage prediction</description><ucd>stat.param</ucd><dataType xsi:type="vs:VOTableType">float</dataType></column><column><name>Vet</name><description>[0.1/0.935] Vetting prediction</description><ucd>stat.param</ucd><dataType xsi:type="vs:VOTableType">float</dataType></column><column><name>_RA</name><description>Positions from TESS Input Catalog v8 (IV/38) (right ascension part)</description><unit>deg</unit><ucd>pos.eq.ra;meta.main</ucd></column><column><name>_DE</name><description>Positions from TESS Input Catalog v8 (IV/38) (declination part)</description><unit>deg</unit><ucd>pos.eq.dec;meta.main</ucd></column></table></schema></tableset></ri:Resource>