J/A+A/708/A215ivo://CDS.VizieR/J/A+A/708/A215CDSBoin T.Casamiquela L.Haywood M.Di Matteo P.Lebreton Y.Uddin M.,Reese D.2026-04-09T16:28:35Z2026-04-09T17:26:05ZCDS support team

CDS, Observatoire de Strasbourg, 11 rue de l'Universite, F-67000 Strasbourg, France

cds-question@unistra.frmilky-way-galaxyphotometrychemical-abundancesstellar-evolutionary-tracksstellar-evolutionary-modelsstellar-agesRecent spectroscopic surveys provide element abundances for large samples of Milky Way stars, from which stellar parameters can be inferred. Stellar ages, among them, are both a notoriously difficult parameter to estimate and a fundamental property for Galactic archaeology studies. We aim to develop a model-driven deep learning approach to age determination, by training neural networks on stellar evolutionary grids. Contrary to the usual data-driven deep learning approach of using prior age estimates as training data, our method has the potential for a wider and less biased range of application. The low computational cost of deep learning methods compared to e.g., bayesian isochrone-fitting allows for a broad analysis of large spectroscopic catalogues. We train multilayer perceptrons on different stellar evolutionary grids to map [M/H], M_G_, (G_BP_-G_RP_) to stellar age tau. We combine Gaia photometry and parallaxes, metallicities and alpha elements from spectroscopic surveys and extinction maps, which are passed through the neural networks to estimate stellar ages. We apply our method to the LAMOST DR10, GALAH DR3 & DR4 and APOGEE DR17 spectroscopic surveys, for which we estimate the ages using the BaSTI tracks, along with other stellar evolutionary models. We leverage this novel technique to study, for the first time, differences in age estimates from several evolutionary grids applied on very large datasets. In addition, we date 13 open clusters and one globular cluster and find a median absolute deviation with literature ages of 0.20Gyr. Along with the stellar ages catalogues from our estimates, we release NEST (Neural Estimator of Stellar Times), a python package to estimate stellar age based on this work and available at https://github.com/star-age/NEST, as well as a web interface https://star-age.github.io. We show that, when using the same evolutionary grid, our method retrieves the same ages as a bayesian approach like SPInS, for only a fraction of the computational cost, with a 60000 speedup factor for a typical star. This model-driven deep learning technique thus opens up the way for broad galactic archeology studies on the largest datasets available today and in the near future with upcoming surveys such as 4MOST.2026A&A...708A.215Bhttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/A+A/708/A215CatalogResearchIsServedByTAP VizieR generic servicerelated-toI/355 : Gaia DR3 Part 1. Main source (Gaia Collaboration, 2022)V/162 : LAMOST DR11 catalogs (Luo+, 2026)J/MNRAS/506/150 : The GALAH+ Survey DR3 (Buder+, 2021)https://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/A+A/708/A215https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/A+A/708/A215http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/A+A/708/A215https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/A+A/708/A215https://vizier.iucaa.in/viz-bin/votable?-source=J/A+A/708/A215http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/A+A/708/A215GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapdefaultJ/A+A/708/A215/lamostlLAMOST low-resolution DR10 stars age cataloguerecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintGaiaDR3Gaia DR3 source ID (source_id)meta.id;meta.mainABPGaia BP-band extinction (ABP)magphys.absorptionfloatARPGaia RP-band extinction (ARP)magphys.absorptionfloatAGGaia G-band extinction (AG)magphys.absorptionfloatAvVisual extinction (Av)magphys.absorptionfloatGBP-GRP0GBP-GRP color extinction corrected (GBP_GRP_0)magphot.color;em.opt.B;em.opt.RfloatGMAGAbsolute G-band magnitude (MG)magphot.magfloat[alpha/Fe]Abundance [alpha/Fe] (alpha_fe)phys.abundfloat[Fe/H]Abundance [Fe/H] (feh)phys.abund.Fefloat[Fe/H]caledScaled Fe/H using Salaris et al. 93 relation (feh_scaled)phys.abund.FefloatloggSurface gravity (logg)phys.gravityfloate_[Fe/H]Uncertainty on [Fe/H] (err_feh)stat.error;phys.abund.Fefloate_[Fe/H]caledUncertainty on scaled [Fe/H] (err_feh_scaled)stat.error;phys.abund.Fefloate_ABPError on ABP (eABP)magstat.errorfloate_ARPError on ARP (eARP)magstat.errorfloate_AGError on AG (eAG)magstat.errorfloate_GMAGError on MG (eMG)magstat.errorfloate_GBP-GRP0Error on GBP_GRP_0 (eBPRP)magstat.errorfloate_[alpha/Fe]Error on [alpha/Fe] (err_alpha_fe)stat.error;phys.abundfloate_logg? Error on logg (logg_err)stat.errorfloatnullableAgeBaSTImeanMean age using a BaSTI-trained Neural Network (Age_BaSTI_mean)Gyrtime.age;stat.meanfloatAgeBaSTImedianMedian age using a BaSTI-trained Neural Network (Age_BaSTI_median)Gyrtime.age;stat.medianfloatAgeBaSTIstdAge standard deviation using a BaSTI-trained Neural Network (Age_BaSTI_std)Gyrstat.stdev;time.agefloatAgeBaSTImodeMode age using a BaSTI-trained Neural Network (Age_BaSTI_mode)Gyrtime.agefloatinDomainBaSTIBoolean flag: is within BaSTI grid domain (1=yes,0=no) (in_domain_BaSTI)meta.codeintAgeMISTmeanMean age using a MIST-trained Neural Network (Age_MIST_mean)Gyrtime.age;stat.meanfloatAgeMISTmedianMedian age using a MIST-trained Neural Network (Age_MIST_median)Gyrtime.age;stat.medianfloatAgeMISTstdAge standard deviation using a MIST-trained Neural Network (Age_MIST_std)Gyrstat.stdev;time.agefloatAgeMISTmodeMode age using a MIST-trained Neural Network (Age_MIST_mode)Gyrtime.agefloatinDomainMISTBoolean flag: is within MIST grid domain (1=yes,0=no) (in_domain_MIST)meta.codeintAgePARSECmeanMean age using a PARSEC-trained Neural Network (Age_PARSEC_mean)Gyrtime.age;stat.meanfloatAgePARSECmedianMedian age using a PARSEC-trained Neural Network (Age_PARSEC_median)Gyrtime.age;stat.medianfloatAgePARSECstdAge standard deviation using a PARSEC-trained Neural Network (Age_PARSEC_std)Gyrstat.stdev;time.agefloatAgePARSECmodeMode age using a PARSEC-trained Neural Network (Age_PARSEC_mode)Gyrtime.agefloatinDomainPARSECBoolean flag: is within PARSEC grid domain (1=yes,0=no) (in_domain_PARSEC)meta.codeintAgeDartmouth_meanMean age using a Dartmouth-trained Neural Network (Age_Dartmouth_mean)Gyrtime.age;stat.meanfloatAgeDartmouthmedianMedian age using a Dartmouth-trained Neural Network (Age_Dartmouth_median)Gyrtime.age;stat.medianfloatAgeDartmouthstdAge standard deviation using a Dartmouth-trained Neural Network (Age_Dartmouth_std)Gyrstat.stdev;time.agefloatAgeDartmouthmodeMode age using a Dartmouth-trained Neural Network (Age_Dartmouth_mode)Gyrtime.agefloatinDomainDartmouthBoolean flag: is within Dartmouth grid domain (1=yes,0=no) (in_domain_Dartmouth)meta.codeintAgeGenevameanMean age using a Geneva-trained Neural Network (Age_Geneva_mean)Gyrtime.age;stat.meanfloatAgeGenevamedianMedian age using a Geneva-trained Neural Network (Age_Geneva_median)Gyrtime.age;stat.medianfloatAgeGenevastdAge standard deviation using a Geneva-trained Neural Network (Age_Geneva_std)Gyrstat.stdev;time.agefloatAgeGenevamodeMode age using a Geneva-trained Neural Network (Age_Geneva_mode)Gyrtime.agefloatinDomainGenevaBoolean flag: is within Geneva grid domain (1=yes,0=no) (in_domain_Geneva)meta.codeintJ/A+A/708/A215/lamostmLAMOST medium-resolution DR10 stars age catalogueGaiaDR3Gaia DR3 source ID (source_id)meta.id;meta.mainrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintABPGaia BP-band extinction (ABP)magphys.absorptionfloatARPGaia RP-band extinction (ARP)magphys.absorptionfloatAGGaia G-band extinction (AG)magphys.absorptionfloatAvVisual extinction (Av)magphys.absorptionfloatGBP-GRP0GBP-GRP color extinction corrected (GBP_GRP_0)magphot.color;em.opt.B;em.opt.RfloatGMAGAbsolute G-band magnitude (MG)magphot.magfloat[alpha/Fe]Abundance [alpha/Fe] (alpha_fe)phys.abundfloat[Fe/H]Abundance [Fe/H] (feh)phys.abund.Fefloat[Fe/H]caledScaled Fe/H using Salaris et al. 93 relation (feh_scaled)phys.abund.FefloatloggSurface gravity (logg)phys.gravityfloate_[Fe/H]Uncertainty on [Fe/H] (err_feh)stat.error;phys.abund.Fefloate_[Fe/H]caledUncertainty on scaled [Fe/H] (err_feh_scaled)stat.error;phys.abund.Fefloate_ABPError on ABP (eABP)magstat.errorfloate_ARPError on ARP (eARP)magstat.errorfloate_AGError on AG (eAG)magstat.errorfloate_GMAGError on MG (eMG)magstat.errorfloate_GBP-GRP0Error on GBP_GRP_0 (eBPRP)magstat.errorfloate_[alpha/Fe]Error on [alpha/Fe] (err_alpha_fe)stat.error;phys.abundfloate_logg? Error on logg (logg_err)stat.errorfloatnullableAgeBaSTImeanMean age using a BaSTI-trained Neural Network (Age_BaSTI_mean)Gyrtime.age;stat.meanfloatAgeBaSTImedianMedian age using a BaSTI-trained Neural Network (Age_BaSTI_median)Gyrtime.age;stat.medianfloatAgeBaSTIstdAge standard deviation using a BaSTI-trained Neural Network (Age_BaSTI_std)Gyrstat.stdev;time.agefloatAgeBaSTImodeMode age using a BaSTI-trained Neural Network (Age_BaSTI_mode)Gyrtime.agefloatinDomainBaSTIBoolean flag: is within BaSTI grid domain (1=yes,0=no) (in_domain_BaSTI)meta.codeintAgeMISTmeanMean age using a MIST-trained Neural Network (Age_MIST_mean)Gyrtime.age;stat.meanfloatAgeMISTmedianMedian age using a MIST-trained Neural Network (Age_MIST_median)Gyrtime.age;stat.medianfloatAgeMISTstdAge standard deviation using a MIST-trained Neural Network (Age_MIST_std)Gyrstat.stdev;time.agefloatAgeMISTmodeMode age using a MIST-trained Neural Network (Age_MIST_mode)Gyrtime.agefloatinDomainMISTBoolean flag: is within MIST grid domain (1=yes,0=no) (in_domain_MIST)meta.codeintAgePARSECmeanMean age using a PARSEC-trained Neural Network (Age_PARSEC_mean)Gyrtime.age;stat.meanfloatAgePARSECmedianMedian age using a PARSEC-trained Neural Network (Age_PARSEC_median)Gyrtime.age;stat.medianfloatAgePARSECstdAge standard deviation using a PARSEC-trained Neural Network (Age_PARSEC_std)Gyrstat.stdev;time.agefloatAgePARSECmodeMode age using a PARSEC-trained Neural Network (Age_PARSEC_mode)Gyrtime.agefloatinDomainPARSECBoolean flag: is within PARSEC grid domain (1=yes,0=no) (in_domain_PARSEC)meta.codeintAgeDartmouth_meanMean age using a Dartmouth-trained Neural Network (Age_Dartmouth_mean)Gyrtime.age;stat.meanfloatAgeDartmouthmedianMedian age using a Dartmouth-trained Neural Network (Age_Dartmouth_median)Gyrtime.age;stat.medianfloatAgeDartmouthstdAge standard deviation using a Dartmouth-trained Neural Network (Age_Dartmouth_std)Gyrstat.stdev;time.agefloatAgeDartmouthmodeMode age using a Dartmouth-trained Neural Network (Age_Dartmouth_mode)Gyrtime.agefloatinDomainDartmouthBoolean flag: is within Dartmouth grid domain (1=yes,0=no) (in_domain_Dartmouth)meta.codeintAgeGenevameanMean age using a Geneva-trained Neural Network (Age_Geneva_mean)Gyrtime.age;stat.meanfloatAgeGenevamedianMedian age using a Geneva-trained Neural Network (Age_Geneva_median)Gyrtime.age;stat.medianfloatAgeGenevastdAge standard deviation using a Geneva-trained Neural Network (Age_Geneva_std)Gyrstat.stdev;time.agefloatAgeGenevamodeMode age using a Geneva-trained Neural Network (Age_Geneva_mode)Gyrtime.agefloatinDomainGenevaBoolean flag: is within Geneva grid domain (1=yes,0=no) (in_domain_Geneva)meta.codeintJ/A+A/708/A215/galah3GALAH DR3 stars age catalogueGaiaDR3Gaia DR3 source ID (source_id)meta.id;meta.main[Fe/H]Abundance [Fe/H] (feh)phys.abund.FefloatrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintABPGaia BP-band extinction (ABP)magphys.absorptionfloatARPGaia RP-band extinction (ARP)magphys.absorptionfloatAGGaia G-band extinction (AG)magphys.absorptionfloatAvVisual extinction (Av)magphys.absorptionfloatGBP-GRP0GBP-GRP color extinction corrected (GBP_GRP_0)magphot.color;em.opt.B;em.opt.RfloatGMAGAbsolute G-band magnitude (MG)magphot.magfloat[alpha/Fe]Abundance [alpha/Fe] (alpha_fe)phys.abundfloat[Fe/H]caledScaled Fe/H using Salaris et al. 93 relation (feh_scaled)phys.abund.FefloatloggSurface gravity (logg)phys.gravityfloate_[Fe/H]Uncertainty on [Fe/H] (err_feh)stat.error;phys.abund.Fefloate_[Fe/H]caledUncertainty on scaled [Fe/H] (err_feh_scaled)stat.error;phys.abund.Fefloate_ABPError on ABP (eABP)magstat.errorfloate_ARPError on ARP (eARP)magstat.errorfloate_AGError on AG (eAG)magstat.errorfloate_GMAGError on MG (eMG)magstat.errorfloate_GBP-GRP0Error on GBP_GRP_0 (eBPRP)magstat.errorfloate_[alpha/Fe]Error on [alpha/Fe] (err_alpha_fe)stat.error;phys.abundfloate_logg? Error on logg (logg_err)stat.errorfloatnullableAgeBaSTImeanMean age using a BaSTI-trained Neural Network (Age_BaSTI_mean)Gyrtime.age;stat.meanfloatAgeBaSTImedianMedian age using a BaSTI-trained Neural Network (Age_BaSTI_median)Gyrtime.age;stat.medianfloatAgeBaSTIstdAge standard deviation using a BaSTI-trained Neural Network (Age_BaSTI_std)Gyrstat.stdev;time.agefloatAgeBaSTImodeMode age using a BaSTI-trained Neural Network (Age_BaSTI_mode)Gyrtime.agefloatinDomainBaSTIBoolean flag: is within BaSTI grid domain (1=yes,0=no) (in_domain_BaSTI)meta.codeintAgeMISTmeanMean age using a MIST-trained Neural Network (Age_MIST_mean)Gyrtime.age;stat.meanfloatAgeMISTmedianMedian age using a MIST-trained Neural Network (Age_MIST_median)Gyrtime.age;stat.medianfloatAgeMISTstdAge standard deviation using a MIST-trained Neural Network (Age_MIST_std)Gyrstat.stdev;time.agefloatAgeMISTmodeMode age using a MIST-trained Neural Network (Age_MIST_mode)Gyrtime.agefloatinDomainMISTBoolean flag: is within MIST grid domain (1=yes,0=no) (in_domain_MIST)meta.codeintAgePARSECmeanMean age using a PARSEC-trained Neural Network (Age_PARSEC_mean)Gyrtime.age;stat.meanfloatAgePARSECmedianMedian age using a PARSEC-trained Neural Network (Age_PARSEC_median)Gyrtime.age;stat.medianfloatAgePARSECstdAge standard deviation using a PARSEC-trained Neural Network (Age_PARSEC_std)Gyrstat.stdev;time.agefloatAgePARSECmodeMode age using a PARSEC-trained Neural Network (Age_PARSEC_mode)Gyrtime.agefloatinDomainPARSECBoolean flag: is within PARSEC grid domain (1=yes,0=no) (in_domain_PARSEC)meta.codeintAgeDartmouth_meanMean age using a Dartmouth-trained Neural Network (Age_Dartmouth_mean)Gyrtime.age;stat.meanfloatAgeDartmouthmedianMedian age using a Dartmouth-trained Neural Network (Age_Dartmouth_median)Gyrtime.age;stat.medianfloatAgeDartmouthstdAge standard deviation using a Dartmouth-trained Neural Network (Age_Dartmouth_std)Gyrstat.stdev;time.agefloatAgeDartmouthmodeMode age using a Dartmouth-trained Neural Network (Age_Dartmouth_mode)Gyrtime.agefloatinDomainDartmouthBoolean flag: is within Dartmouth grid domain (1=yes,0=no) (in_domain_Dartmouth)meta.codeintAgeGenevameanMean age using a Geneva-trained Neural Network (Age_Geneva_mean)Gyrtime.age;stat.meanfloatAgeGenevamedianMedian age using a Geneva-trained Neural Network (Age_Geneva_median)Gyrtime.age;stat.medianfloatAgeGenevastdAge standard deviation using a Geneva-trained Neural Network (Age_Geneva_std)Gyrstat.stdev;time.agefloatAgeGenevamodeMode age using a Geneva-trained Neural Network (Age_Geneva_mode)Gyrtime.agefloatinDomainGenevaBoolean flag: is within Geneva grid domain (1=yes,0=no) (in_domain_Geneva)meta.codeintJ/A+A/708/A215/galah4GALAH DR4 stars ages catalogueGaiaDR3Gaia DR3 source ID (source_id)meta.id;meta.mainrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintABPGaia BP-band extinction (ABP)magphys.absorptionfloatARPGaia RP-band extinction (ARP)magphys.absorptionfloatAGGaia G-band extinction (AG)magphys.absorptionfloatAvVisual extinction (Av)magphys.absorptionfloatGBP-GRP0GBP-GRP color extinction corrected (GBP_GRP_0)magphot.color;em.opt.B;em.opt.RfloatGMAGAbsolute G-band magnitude (MG)magphot.magfloat[alpha/Fe]Abundance [alpha/Fe] (alpha_fe)phys.abundfloat[Fe/H]Abundance [Fe/H] (feh)phys.abund.Fefloat[Fe/H]caledScaled Fe/H using Salaris et al. 93 relation (feh_scaled)phys.abund.FefloatloggSurface gravity (logg)phys.gravityfloate_[Fe/H]Uncertainty on [Fe/H] (err_feh)stat.error;phys.abund.Fefloate_[Fe/H]caledUncertainty on scaled [Fe/H] (err_feh_scaled)stat.error;phys.abund.Fefloate_ABPError on ABP (eABP)magstat.errorfloate_ARPError on ARP (eARP)magstat.errorfloate_AGError on AG (eAG)magstat.errorfloate_GMAGError on MG (eMG)magstat.errorfloate_GBP-GRP0Error on GBP_GRP_0 (eBPRP)magstat.errorfloate_[alpha/Fe]Error on [alpha/Fe] (err_alpha_fe)stat.error;phys.abundfloate_logg? Error on logg (logg_err)stat.errorfloatnullableAgeBaSTImeanMean age using a BaSTI-trained Neural Network (Age_BaSTI_mean)Gyrtime.age;stat.meanfloatAgeBaSTImedianMedian age using a BaSTI-trained Neural Network (Age_BaSTI_median)Gyrtime.age;stat.medianfloatAgeBaSTIstdAge standard deviation using a BaSTI-trained Neural Network (Age_BaSTI_std)Gyrstat.stdev;time.agefloatAgeBaSTImodeMode age using a BaSTI-trained Neural Network (Age_BaSTI_mode)Gyrtime.agefloatinDomainBaSTIBoolean flag: is within BaSTI grid domain (1=yes,0=no) (in_domain_BaSTI)meta.codeintAgeMISTmeanMean age using a MIST-trained Neural Network (Age_MIST_mean)Gyrtime.age;stat.meanfloatAgeMISTmedianMedian age using a MIST-trained Neural Network (Age_MIST_median)Gyrtime.age;stat.medianfloatAgeMISTstdAge standard deviation using a MIST-trained Neural Network (Age_MIST_std)Gyrstat.stdev;time.agefloatAgeMISTmodeMode age using a MIST-trained Neural Network (Age_MIST_mode)Gyrtime.agefloatinDomainMISTBoolean flag: is within MIST grid domain (1=yes,0=no) (in_domain_MIST)meta.codeintAgePARSECmeanMean age using a PARSEC-trained Neural Network (Age_PARSEC_mean)Gyrtime.age;stat.meanfloatAgePARSECmedianMedian age using a PARSEC-trained Neural Network (Age_PARSEC_median)Gyrtime.age;stat.medianfloatAgePARSECstdAge standard deviation using a PARSEC-trained Neural Network (Age_PARSEC_std)Gyrstat.stdev;time.agefloatAgePARSECmodeMode age using a PARSEC-trained Neural Network (Age_PARSEC_mode)Gyrtime.agefloatinDomainPARSECBoolean flag: is within PARSEC grid domain (1=yes,0=no) (in_domain_PARSEC)meta.codeintAgeDartmouth_meanMean age using a Dartmouth-trained Neural Network (Age_Dartmouth_mean)Gyrtime.age;stat.meanfloatAgeDartmouthmedianMedian age using a Dartmouth-trained Neural Network (Age_Dartmouth_median)Gyrtime.age;stat.medianfloatAgeDartmouthstdAge standard deviation using a Dartmouth-trained Neural Network (Age_Dartmouth_std)Gyrstat.stdev;time.agefloatAgeDartmouthmodeMode age using a Dartmouth-trained Neural Network (Age_Dartmouth_mode)Gyrtime.agefloatinDomainDartmouthBoolean flag: is within Dartmouth grid domain (1=yes,0=no) (in_domain_Dartmouth)meta.codeintAgeGenevameanMean age using a Geneva-trained Neural Network (Age_Geneva_mean)Gyrtime.age;stat.meanfloatAgeGenevamedianMedian age using a Geneva-trained Neural Network (Age_Geneva_median)Gyrtime.age;stat.medianfloatAgeGenevastdAge standard deviation using a Geneva-trained Neural Network (Age_Geneva_std)Gyrstat.stdev;time.agefloatAgeGenevamodeMode age using a Geneva-trained Neural Network (Age_Geneva_mode)Gyrtime.agefloatinDomainGenevaBoolean flag: is within Geneva grid domain (1=yes,0=no) (in_domain_Geneva)meta.codeintJ/A+A/708/A215/apogeeAPOGEE DR17 stars age catalogueGMAGAbsolute G-band magnitude (MG)magphot.magfloatrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintGaiaDR3Gaia DR3 source ID (source_id)meta.id;meta.mainABPGaia BP-band extinction (ABP)magphys.absorptionfloatARPGaia RP-band extinction (ARP)magphys.absorptionfloatAGGaia G-band extinction (AG)magphys.absorptionfloatAvVisual extinction (Av)magphys.absorptionfloatGBP-GRP0GBP-GRP color extinction corrected (GBP_GRP_0)magphot.color;em.opt.B;em.opt.Rfloat[alpha/Fe]Abundance [alpha/Fe] (alpha_fe)phys.abundfloat[Fe/H]Abundance [Fe/H] (feh)phys.abund.Fefloat[Fe/H]caledScaled Fe/H using Salaris et al. 93 relation (feh_scaled)phys.abund.FefloatloggSurface gravity (logg)phys.gravityfloate_[Fe/H]Uncertainty on [Fe/H] (err_feh)stat.error;phys.abund.Fefloate_[Fe/H]caledUncertainty on scaled [Fe/H] (err_feh_scaled)stat.error;phys.abund.Fefloate_ABPError on ABP (eABP)magstat.errorfloate_ARPError on ARP (eARP)magstat.errorfloate_AGError on AG (eAG)magstat.errorfloate_GMAGError on MG (eMG)magstat.errorfloate_GBP-GRP0Error on GBP_GRP_0 (eBPRP)magstat.errorfloate_[alpha/Fe]Error on [alpha/Fe] (err_alpha_fe)stat.error;phys.abundfloate_logg? Error on logg (logg_err)stat.errorfloatnullableAgeBaSTImeanMean age using a BaSTI-trained Neural Network (Age_BaSTI_mean)Gyrtime.age;stat.meanfloatAgeBaSTImedianMedian age using a BaSTI-trained Neural Network (Age_BaSTI_median)Gyrtime.age;stat.medianfloatAgeBaSTIstdAge standard deviation using a BaSTI-trained Neural Network (Age_BaSTI_std)Gyrstat.stdev;time.agefloatAgeBaSTImodeMode age using a BaSTI-trained Neural Network (Age_BaSTI_mode)Gyrtime.agefloatinDomainBaSTIBoolean flag: is within BaSTI grid domain (1=yes,0=no) (in_domain_BaSTI)meta.codeintAgeMISTmeanMean age using a MIST-trained Neural Network (Age_MIST_mean)Gyrtime.age;stat.meanfloatAgeMISTmedianMedian age using a MIST-trained Neural Network (Age_MIST_median)Gyrtime.age;stat.medianfloatAgeMISTstdAge standard deviation using a MIST-trained Neural Network (Age_MIST_std)Gyrstat.stdev;time.agefloatAgeMISTmodeMode age using a MIST-trained Neural Network (Age_MIST_mode)Gyrtime.agefloatinDomainMISTBoolean flag: is within MIST grid domain (1=yes,0=no) (in_domain_MIST)meta.codeintAgePARSECmeanMean age using a PARSEC-trained Neural Network (Age_PARSEC_mean)Gyrtime.age;stat.meanfloatAgePARSECmedianMedian age using a PARSEC-trained Neural Network (Age_PARSEC_median)Gyrtime.age;stat.medianfloatAgePARSECstdAge standard deviation using a PARSEC-trained Neural Network (Age_PARSEC_std)Gyrstat.stdev;time.agefloatAgePARSECmodeMode age using a PARSEC-trained Neural Network (Age_PARSEC_mode)Gyrtime.agefloatinDomainPARSECBoolean flag: is within PARSEC grid domain (1=yes,0=no) (in_domain_PARSEC)meta.codeintAgeDartmouth_meanMean age using a Dartmouth-trained Neural Network (Age_Dartmouth_mean)Gyrtime.age;stat.meanfloatAgeDartmouthmedianMedian age using a Dartmouth-trained Neural Network (Age_Dartmouth_median)Gyrtime.age;stat.medianfloatAgeDartmouthstdAge standard deviation using a Dartmouth-trained Neural Network (Age_Dartmouth_std)Gyrstat.stdev;time.agefloatAgeDartmouthmodeMode age using a Dartmouth-trained Neural Network (Age_Dartmouth_mode)Gyrtime.agefloatinDomainDartmouthBoolean flag: is within Dartmouth grid domain (1=yes,0=no) (in_domain_Dartmouth)meta.codeintAgeGenevameanMean age using a Geneva-trained Neural Network (Age_Geneva_mean)Gyrtime.age;stat.meanfloatAgeGenevamedianMedian age using a Geneva-trained Neural Network (Age_Geneva_median)Gyrtime.age;stat.medianfloatAgeGenevastdAge standard deviation using a Geneva-trained Neural Network (Age_Geneva_std)Gyrstat.stdev;time.agefloatAgeGenevamodeMode age using a Geneva-trained Neural Network (Age_Geneva_mode)Gyrtime.agefloatinDomainGenevaBoolean flag: is within Geneva grid domain (1=yes,0=no) (in_domain_Geneva)meta.codeint