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Photometric Stellar Parameters for 195,478 Kepler Input Catalog (KIC) Stars

T0 review · 3 major / 6 minor · reviewed 2026-08-11 · deepseek-v4-flash

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Pith's one-line read Using photometric colors and random-forest training on LAMOST spectroscopy, this paper derives atmospheric parameters for 195,478 Kepler Input Catalog stars — 97% of the catalog — with 0.12 dex metallicity, 100 K temperature, and 0.2 dex…

desk verdict Useful KIC catalog with a validation gap: the extinction map leaks LAMOST labels into the training features, so quoted uncertainties on unlabeled stars are probably optimistic. read the letter →

arxiv 2412.16930 v3 pith:R5RA7WAD submitted 2024-12-22 astro-ph.SR astro-ph.EPastro-ph.GA

Bowen Zhang , Yang Huang , Timothy C. Beers , Kai Xiao , Jifeng Liu , Lei Jia , Henggeng Han , Zhirui Li
show 4 more authors
Chuanjie Zheng Yongkang Sun Ruifeng Shi Hongrui Gu
This is my paper · ORCID
classification astro-ph.SRastro-ph.EPastro-ph.GA
keywords KeplerInputCatalogphotometricstellarparametersrandomforestregressionstar-pairextinctionmethodGaiaXPspectraStrömgrenphotometryisochronefittingmetallicity
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The Kepler Input Catalog (KIC) lists about 200,000 stars targeted by the planet-hunting Kepler mission, but only around half have spectroscopically measured atmospheric parameters. This paper claims to close that gap: by training random-forest regressors that map photometric colors — including the KIS $U$-band and Strömgren colors synthesized from Gaia XP spectra — to spectroscopic parameters from LAMOST DR10, it derives effective temperature $T_{\rm eff}$, surface gravity $\log g$, and metallicity $[{\rm Fe/H}]$ for 195,478 KIC stars, 97% of the catalog, with $1\sigma$ uncertainties of 100 K, 0.2 dex, and 0.12 dex respectively. A new star-pair 3D extinction map of the Kepler field supplies the reddening corrections that make the dereddened colors reliable. These parameters then feed a Bayesian isochrone fit with PARSEC models to estimate ages, masses, radii, and gravities, validated against APOGEE, CKS, open clusters, and asteroseismic data. If correct, the catalog turns the Kepler field into a nearly fully characterized stellar sample for exoplanet-host and stellar-evolution studies.

What carries the argument

The machinery has three linked parts. The first is the star-pair extinction method: for each target star, stars from a low-extinction reference sample ($E(B-V) < 0.01$ from Green et al. 2019) with similar $T_{\rm eff}$, $\log g$, and $[{\rm Fe/H}]$ provide an intrinsic color $(BP-RP)_0$, and the difference between observed and intrinsic color gives $E(BP-RP)$; these per-star reddenings are interpolated onto a 10-arcmin, 20-pc grid to form a 3D map of the Kepler field. The second is random-forest regression, trained separately for main-sequence, turn-off, giant, binary, and blue-star classes, relating dereddened colors — $(U-BP)_0$ and Strömgren $m_1$ for metallicity, $(b-y)_0$ with $[{\rm Fe/H}]$ for $T_{\rm eff}$, $(U-BP)_0$ with $[{\rm Fe/H}]$ for $\log g$ — to LAMOST DR10 spectroscopic labels. The third is Bayesian isochrone fitting with PARSEC models, which converts the photometric atmospheric parameters plus absolute magnitude and $(BP-RP)_0$ into posterior distributions of age, mass, radius, and $\log g$. The parameter-sensitive colors that carry the metallicity signal are the KIS $U$-band from the Kepler-INT Survey and Strömgren $v$, $b$, $y$ magnitudes synthesized from Gaia XP spectra via GaiaXPy.

What would settle it

Take a sample of KIC stars spanning the full $T_{\rm eff}$–$\log g$–$[{\rm Fe/H}]$ range that have high-resolution spectroscopy from an independent survey not used in training (for example, Keck/HIRES or ultra-violet echelle spectra), and compare the photometric $[{\rm Fe/H}]$, $T_{\rm eff}$, and $\log g$ with the high-resolution values. If the median offsets exceed the quoted 0.12 dex, 100 K, and 0.2 dex, or if the scatter grows with $(BP-RP)_0$ toward cool stars, the central claim fails. A simpler check: for a single line of sight where stars at the same distance are identified (e.g., a well-studied open cluster like NGC 6791), the star-pair $E(BP-RP)$ values must be consistent to well under 0.01 mag; larger internal scatter would falsify the intrinsic-color assumption.

Watch

Extended reading notes

Core claim

The paper's central claim is that narrow- and medium-band photometric colors, most importantly the KIS $U$-band color $(U-BP)_0$ and the Strömgren index $m_1 \equiv (v-b)_0 - (b-y)_0$ synthesized from Gaia XP spectra, carry enough metallicity information that a random-forest model trained on LAMOST DR10 spectroscopic labels can predict $[{\rm Fe/H}]$ to about 0.10–0.12 dex precision over most of the Kepler field, with comparable performance for $T_{\rm eff}$ (about 100 K) and $\log g$ (about 0.2 dex). Dereddening that makes this possible comes from a star-pair extinction map of the Kepler field built from low-extinction reference stars, which the paper argues is more precise than the Green et al. (2019) map, with cluster-member scatter below 0.01 mag. The trained relations are applied separately to five luminosity classes, and Monte Carlo simulations propagate photometric and extinction errors into per-star uncertainties. From the photometric parameters, PARSEC isochrones are fitted in a Bayesian way to yield mass, radius, $\log g$, and age, and external comparisons (APOGEE DR17, CKS DR2, wide binaries, four open clusters, SD18, APOKASC) give the quoted precisions for dwarfs, giants, and turn-off stars. The resulting public catalog covers 195,478 stars, including a separate lower-reliability section for M-type stars.

Load-bearing premise

The load-bearing premise is that stars with the same effective temperature, surface gravity, and metallicity have the same intrinsic colors, so a reference sample of low-extinction stars (Green et al. 2019, $E(B-V) < 0.01$) can calibrate the intrinsic-color model; if that reference selection is biased, every extinction-corrected color in the catalog is systematically off and the trained relations inherit the error.

Editorial extensions

If this is right

  • Nearly the entire Kepler field (195,478 of roughly 200,000 KIC stars) becomes usable for population studies that require metallicities, temperatures, and gravities, without waiting for additional spectroscopy.
  • The star-pair 3D extinction map gives per-star reddening for the Kepler field at 10-arcmin angular and 20-pc distance resolution, an improvement in internal precision over the Green et al. (2019) map for cluster members.
  • Exoplanet host stars in KIC can now be characterized homogeneously, so studies of planet occurrence versus stellar metallicity and the radius gap can be carried out on a nearly complete sample.
  • Turn-off star ages from the Bayesian isochrone fitting carry about 20% precision, which supports galactic archaeology and age–rotation studies in the Kepler field.
  • The synthetic Strömgren colors derived from Gaia XP spectra make the whole procedure portable to any field overlapping Gaia XP and a training spectroscopic survey, not just Kepler.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • Beyond the paper: the luminosity-class splits that improve accuracy mean the method's precision is likely worst near class boundaries, especially between main-sequence and binary stars, so users of the catalog should treat boundary stars' parameters as less reliable than the headline uncertainties suggest.
  • Beyond the paper: since the training set is LAMOST-dominated, the quoted 0.12 dex metallicity precision probably does not extend to the metal-poor tail ([Fe/H] < −2) or to the coolest M dwarfs, which the paper itself flags as lower reliability.
  • Beyond the paper: the same color–parameter pipeline could be retargeted to other narrow-band surveys, such as SkyMapper or SAGES, to produce full-census stellar parameter catalogs over much larger footprints, using the open-cluster and wide-binary checks as a validation template.
  • Beyond the paper: an unstated testable consequence is that asteroseismic masses of red giants, which are nearly model-independent, could calibrate the mass-loss parameter in the isochrone fitting, potentially reducing the reported 0.14 solar-mass giant-mass scatter.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 6 minor

Summary. The paper derives photometric stellar atmospheric parameters (Teff, log g, [Fe/H]) for roughly 195,000 Kepler Input Catalog stars using KIS U-band photometry and Strömgren photometry synthesized from Gaia XP spectra, with random-forest relations trained on LAMOST DR10 labels. A three-dimensional extinction map for the Kepler field is constructed with the 'star-pair' method, and the dereddened colors are used to train and apply the photometric relations. The paper also derives masses, radii, ages, and log g via PARSEC isochrone fitting and validates the results against APOGEE, CKS, SD18, APOKASC, wide binaries, and open clusters. The central claims are coverage of 97% of KIC stars and typical uncertainties of 0.1 dex in [Fe/H], 100 K in Teff, and 0.2 dex in log g.

Significance. If the uncertainty claims hold, this catalog would be a valuable homogeneous resource for exoplanet host studies, stellar activity, and asteroseismology, extending spectroscopic-quality parameters to most KIC stars. The paper's strengths include extensive external comparisons, cluster-based extinction checks, Monte Carlo uncertainty estimates, and a public catalog release at Zenodo. However, the validation is compromised by the coupling between the extinction-map construction and the LAMOST labels used as training data; the quoted precision therefore may not transfer to the stars without spectroscopy. The significance of the work depends on whether the authors can demonstrate that the validation sample is truly independent of the extinction-map construction and the training set.

major comments (3)
  1. [§3 and §4.1] The 3D extinction map is constructed from E(BP−RP) values (Eq. 1) that are derived for each of the 126,277 LAMOST targets from the difference between the observed BP−RP and an intrinsic color predicted from that star's own LAMOST Teff, log g, and [Fe/H]. The dereddened colors used as random-forest features for the photometric parameter relations are therefore functions of the label being predicted. For the ~195,000 KIC stars without LAMOST spectroscopy, E(BP−RP) comes from a 10-arcmin/20-pc interpolated map and contains no individual label information. This creates a training/prediction distribution mismatch: the random forests are trained under conditions where (BP−RP)0 is essentially the intrinsic color predicted from the true labels, while at prediction time it is noisy and label-free. The quoted validation against APOGEE/CKS does not remove this problem if those stars also have LAMOST spectra used in the map construction. Please demonstrate that performance is not inflated, for example by constructing the extinction map from a subset of LAMOST stars, dereddening a held-out LAMOST sample using only the interpolated map, and reporting the scatter for that held-out sample; the same should be done for the APOGEE/CKS validation stars.
  2. [§4.1 and §4.4] The internal consistency test (Figure 4) and the Monte Carlo uncertainty validation (right panel of Figure 12) are not independent checks. The KIS and Gaia-XP metallicity estimates share the same extinction map and the same LAMOST training labels, so correlated errors can reduce the observed 0.12 dex scatter below the true precision for unlabeled stars. Similarly, the comparison of MC uncertainties with APOGEE dispersion in Figure 12 is only meaningful if the APOGEE stars were not used in either the extinction-map construction or the training of the relations; the paper does not state this. Please report the scatter and the MC uncertainties for a sample that is fully disjoint from both the extinction-map targets and the training set, and specify the overlap between APOGEE/CKS stars and the LAMOST sample used in Section 3.
  3. [§4.4 and §5] The Monte Carlo uncertainty estimates sample photometric and extinction noise, but they do not include the systematic error in the star-pair intrinsic-color model (Section 3). If that model is biased, the bias enters every dereddened color and therefore every star in the catalog, and the random uncertainties will underestimate the true error. The open-cluster comparison (Figure A2) checks internal precision and the median extinction level, but it does not provide a per-star test of the intrinsic-color model. Please quantify the sensitivity of the derived parameters to a plausible bias in E(BP−RP) (e.g., 0.01–0.02 mag) and, if possible, validate the extinction map against stars with independent spectroscopic reddening estimates that were not used in the map construction.
minor comments (6)
  1. [§5.2] The sentence reporting the isochrone log g offsets contains a duplicated phrase: 'and (isochrone fitting minus APOGEE)' appears twice before the LAMOST offset is given.
  2. [§4.1, Table 3] The text states that KIS photometry yielded photometric metallicities for 179,413 stars, while Table 3 lists 179,133 for the KIS U-band photometry; these numbers should be reconciled.
  3. [§4.1 footnote] The paper should specify the actual reddening coefficients and the formulas used to deredden (U−BP)0 and the Strömgren colors from E(BP−RP), rather than only citing an online source, so that catalog users can reproduce the dereddening.
  4. [Abstract and §6.1] The abstract's quoted uncertainties of 0.1 dex, 100 K, and 0.2 dex should be qualified as applying to A/F/G/K stars; Section 6.1 reports substantially larger offsets and dispersions for M-type stars, and those are not covered by the headline precision.
  5. [§6.1] There is a typo: 'ue to the limited accuracy' should read 'Due to the limited accuracy'.
  6. [Figure 14 caption] The caption reads 'The red-dashed ine' and should read 'The red-dashed line'; the same typo appears near the end of Section 3 and in Figure A1's caption.

Circularity Check

1 steps flagged · score 4.0 of 10

Extinction map built from LAMOST labels dereddens the same training and validation stars' colors, so the quoted 0.12 dex precision is partly label-injected; the central catalog values are still externally anchored.

  1. fitted input called prediction [Section 3 (star-pair extinction) feeding Section 4.1 ([Fe/H] = f((U-BP)0,(BP-RP)0))]
    "The extinction values for the target stars E(BP − RP) are measured from the difference between the observed color BP − RP and intrinsic color (BP − RP)0. The latter is derived ... based on the random forest machine-learning fitting technique. ... we adopt the random forest machine-learning method to model the relations [Fe/H] = f((U − BP)0, (BP − RP)0)."

    For the 126,277 LAMOST targets, E(BP-RP) equals the observed color minus the intrinsic color predicted from each star's own LAMOST Teff, log g, and [Fe/H]. The dereddened color (BP-RP)0 used to train the [Fe/H] random forest is therefore, by construction, the intrinsic color predicted from that star's own LAMOST labels. The feature set for training and validation stars thus encodes the target label, so the internal KIS-vs-Gaia-syn scatter of 0.12 dex (claimed intrinsic precision 0.08 dex) and the APOGEE comparison partly measure label consistency rather than the method's error on label-free KIC stars. The catalog values are not forced to equal LAMOST labels, but the quoted uncertainties are partially circular.

full rationale

The central calibration is legitimate supervised learning: LAMOST DR10 labels are the training targets and the SP extinction method is described in detail and checked against open clusters, so the citation to Yuan et al. 2013 is not load-bearing. The internal chaining that uses photometric [Fe/H] as an input to the Teff and log g relations does not define those target labels and is not circular. The one substantive concern is label injection through the extinction map: for the very stars used to train and validate the photometric relations, the dereddened colors are functions of the same LAMOST labels that are the prediction targets, because E(BP-RP) is derived from those labels before interpolation into the 3D map. This makes the internal precision estimate and part of the APOGEE/CKS validation partly self-referential, and it is not acknowledged in the uncertainty analysis. However, the predictions for the roughly 195,000 KIC stars do not reduce to LAMOST labels by equality, the SP extinction map is independently validated with open cluster members, and independent anchors such as CKS, SD18, APOKASC, and wide binaries support the broader catalog. The central derivation is therefore not a tautology; the circularity is partial and concentrated in the claimed atmospheric-parameter uncertainties rather than in the existence of the catalog.

Assumptions & free parameters 4 free parameters · 5 assumptions · 0 invented entities

The central catalog claim rests on the star-pair extinction assumption, the accuracy of LAMOST training labels, the fidelity of Gaia XP synthesized Strömgren photometry, the [Fe/H]-[M/H] conversion, and the PARSEC model grid. No physical entities are invented. Free parameters include empirically chosen class cuts and reference box sizes, the fitted [alpha/Fe]-[Fe/H] polynomial, and per-cell interpolation choices.

free parameters (4)
  • Star-pair reference box sizes = Empirically chosen; not stated precisely
    Section 3: box sizes for selecting reference stars (Teff within 130 K, log g 0.06 dex, [Fe/H] 0.06 dex) are 'empirically determined'. They set the sample size and color model for extinction estimates, which propagate into all dereddened colors.
  • Luminosity class cuts in the CMD = Empirical: giants and MS with (BP-RP)0 < 1.8, binaries, turn-off, blue with (BP-RP)0 < 0.4
    Section 4.1: 'the cuts to select these classes are empirically determined'. They define the training subsets for metallicity, Teff, and log g relations.
  • [alpha/Fe]-[Fe/H] polynomial coefficients = a0-a6 in Table 2
    Section 5.1: fitted to APOGEE [alpha/H] and [Fe/H] to convert [Fe/H] to [M/H] in Eq. 4. This calibration enters the isochrone fitting metallicity.
  • Per-cell extinction interpolation choice = Cubic or Gaussian error function, chosen per grid by R^2
    Section 3: 'the method demonstrating superior goodness of fit, as measured by the coefficient of determination, was adopted'. This choice affects the E(BP-RP) values for every star.
assumptions (5)
  • domain assumption Stars with similar Teff, log g, and [Fe/H] have analogous intrinsic colors
    Section 3, central idea of the star-pair method; the extinction map and all dereddened colors depend on this.
  • domain assumption LAMOST DR10 spectroscopic parameters are accurate training targets
    Section 4: all photometric relations are trained on LAMOST DR10 spectra; systematic LAMOST errors directly become systematic photometric parameter errors, as acknowledged for the log g offset.
  • domain assumption Gaia XP synthesized Strömgren photometry via GaiaXPy is a faithful representation of the real Strömgren system
    Section 2.1: synthetic v,b,y magnitudes are generated from XP spectra; any synthesis bias propagates into the KIS-Gaia comparison and the Teff/log g relations.
  • domain assumption The [Fe/H] to [M/H] conversion with the fitted [alpha/Fe] relation is valid for all KIC stars
    Section 5.1 Eq. 4 and Table 2; the polynomial is fitted to APOGEE data and assumes similar alpha-enhancement behavior across the sample.
  • domain assumption PARSEC isochrones with Reimers mass loss eta=0.2 describe Kepler field stellar populations
    Section 5.1; isochrone fitting assumes the stellar models and the fixed mass-loss parameter; the authors note giant masses are sensitive to this.

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Pith. "Pith review of Photometric Stellar Parameters for 195,478 Kepler Input Catalog (KIC) Stars." pith.science (2026). https://pith.science/paper/R5RA7WAD

@misc{pith2026241216930,
  author       = {Pith},
  title        = {Pith review of: Photometric Stellar Parameters for 195,478 Kepler Input Catalog (KIC) Stars},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/R5RA7WAD}},
  note         = {Machine review of arXiv:2412.16930}
}
abstract

The stellar atmospheric parameters and physical properties of stars in the Kepler Input Catalog (KIC) are of great significance for the study of exoplanets, stellar activity, and asteroseismology. However, despite extensive effort over the past decades, accurate spectroscopic estimates of these parameters are available for only about half of the stars in the full KIC catalog. In our work, by training relationships between photometric colors and spectroscopic stellar parameters from Gaia DR3, the Kepler Issac-Newton Survey, LAMOST DR10, and APOGEE DR17, we have obtained atmospheric-parameter estimates for over 195,000 stars, accounting for 97$\%$ of the total sample of KIC stars. We obtain 1$\sigma$ uncertainties of 0.1 dex on metallicity [Fe/H], 100 K on effective temperature $T_{\rm eff}$, and 0.2 dex on surface gravity log $g$. In addition, based on these atmospheric parameters, we estimated the ages, masses, radii, and surface gravities of these stars using the commonly adopted isochrone-fitting approach. External comparisons indicate that the resulting precision for turn-off stars is 20$\%$ in age; for dwarf stars, it is 0.07 $M_{\odot}$ in mass, 0.05 $R_{\odot}$ in radius, and 0.12 dex in surface gravity; and for giant stars, it is 0.14 $M_{\odot}$ in mass, 0.73 $R_{\odot}$ in radius, and 0.11 dex in surface gravity.

Figures

Figures reproduced from arXiv: 2412.16930 by the authors.

Figure 1
Figure 1. Depth (left panel) and median E(B − V ) (right panel) of the 3-D reddening map toward Kepler field, coded by the color bars shown to the right of each panel [PITH_FULL_IMAGE:figures/full_fig_p006_1.png] view at source ↗
Figure 2
Figure 2. Color–absolute magnitude diagram of the train￾ing sample defined in Section 4.1, coded by LAMOST metal￾licity, as shown in color bar to the right. The dashed lines represent the cuts to separate different types of stars, i.e., the main-sequence (MS) stars, binary stars, giant stars, turn-off stars, and blue stars with (BP − RP)0 < 0.40. KIC stars using the model trained with KIS photom￾etry, and for 189,727 stars us… view at source ↗
Figure 3
Figure 3. Distributions of the training-sample main-sequence stars (left column of panels) and giant stars (right column of panels) in the (U − BP)0 versus (BP − RP)0 plane (top column) and the [m1] versus (BP − RP)0 plane (right column), coded by LAMOST metallicity ([Fe/H]), as shown by the color bars to the right of each panel. The dashed lines represent equal-metallicity sequences ranging from +0.5 (up) to −1.0 (bottom pan… view at source ↗
Figures from the paper (15 more)
Figure 4
Figure 4. Figure 4: Comparison of photometric-metallicity estimates derived from KIS photometry with those having synthesized Str¨omgren from Gaia XP spectra. The red-dashed line is the one-to-one line. The color bar at right codes the number density of stars. The numbers of stars, mean o…
Figure 5
Figure 5. Figure 5: Upper panels: Comparison of photometric metallicity estimates from the KIS photometry with those from APOGEE DR17 for the full sample (left panel), main-sequence stars (middle panels) and giant stars (right panels). The red-dashed lines are the one-to-one lines. The nu…
Figure 6
Figure 6. Figure 6: Similar to [PITH_FULL_IMAGE:figures/full_fig_p008_6.png]
Figure 7
Figure 7. Figure 7: Comparison of photometric [Fe/H] estimates between wide binary members. Left panel: Comparison of our method based on synthetic photometric data generated from Gaia XP spectra. Right panel: Our method based on KIS photometric data. The red-dashed lines are the one-to-o…
Figure 8
Figure 8. Figure 8: The relations between Teff and color for dwarf stars (including main-sequence stars, turn-off stars and blue stars, shown in left panel) and giants (right panel). The Teff data is adopted from LAMOST DR10, and the [Fe/H] data is from our photometric estimates. The numb…
Figure 9
Figure 9. Figure 9: Comparison of Teff obtained by our method with that from CKS DR2 (left column of panels for dwarf stars) and APOGEE DR17 (right column of panels for giant stars). The red-dashed lines in the upper panels are the one-to-one lines. The numbers of stars, mean offset, and …
Figure 10
Figure 10. Figure 10: The relations between log g −(U −BP)0 and photometric-metallicity estimates for main-sequence stars (left panel) and giant stars (right panel). The log g data is from LAMOST DR10 and the metallicities are obtained by our photometric estimates. The numbers of stars are…
Figure 11
Figure 11. Figure 11: Comparision of log g estimates obtained by our method with CKS DR2 (left column of panels for dwarf stars) and APOGEE DR17 (right column of panels for giant stars). The red-dashed lines in the upper panels are the one-to-one lines. The numbers of stars, mean offset, a…
Figure 12
Figure 12. Figure 12: Left panel: An example of the distribution of final photometric estimates of [Fe/H] yielded by the Monte Carlo simulations. The median value of this distribution is marked by a dashed-green line and the estimate by LAMOST is marked by a red-dashed line. Right panel: C…
Figure 13
Figure 13. Figure 13: Comparision of log g obtained by the isochrone-fitting method with APOGEE DR17 (left column of panels) and LAMOST DR10 (right column of panels). The red-dashed lines in the upper panels are the one-to-one lines. The numbers of stars, mean offset, and dispersion are pr…
Figure 14
Figure 14. Figure 14: Comparisons of stellar mass (left panel) and age (right panel) estimates between this work and Sanders & Das (2018, hereafter SD18) for, respectively, nearly 24,000 main-sequence stars and 14,000 main-sequence turn-off stars in common. The red-dashed ine in the left p…
Figure 15
Figure 15. Figure 15: Age distributions for member stars of the four open clusters (NGC 6791, NGC 6811, NGC 6819, and NGC 6866) in the Kepler field. The blue lines represent the ages derived in this work, while the orange lines indicate the ages from SD18. The mean and dispersion of these …
Figure 16
Figure 16. Figure 16: Comparisons of surface gravity (left panel), mass (middle panel) and radius (right panel) estimates between this work and the CKS survey. The numbers of stars, mean offset (this work minus CKS), and scatter are marked in the upper left of each panel. The red-dashed li…
Figure 17
Figure 17. Figure 17: Similar to [PITH_FULL_IMAGE:figures/full_fig_p016_17.png]
Figure 18
Figure 18. Figure 18: Distribution of KIC stars (orange dots) without reliable parameter estimates on the color–G-band absolute mag￾nitude diagram. The background gray dots represent stars with well-determined atmospheric and physical parameters [PITH_FULL_IMAGE:figures/full_fig_p018_18.png]

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