tokens: results of both the binary pipeline ( Fig. 2 ) and the main GALAH pipeline ( Fig. B.1 ), confirming their close agreement. We observe some trends and biases in these figures, such as the inconsistency for the lowest metallicities in the bottom panel of Fig. 2 , which are a consequence of both the flexibility of the The Cannon model and the adequacy of the training set,where it is difficult to ensure equal representation of spectra in all bins of the modelled parameter space (see Sect. 3.3.1 in Buder et al. 2018 ). 4.2 Photometric validation In this validation check and in Sect. 4.3 , we used the benchmark validation sample, which is a subset of GALAH objects withexternal information about the temperature from the infrared flux method (IRFM; Casagrande et al. 2019 ) and radii (asteroseismology; Stello et al. 2017 ; Sharma et al. 2019 ). This sample of 620 giant stars is therefore suitable for benchmark testing, and is dominated by stars from K2 campaigns C1 and C6 ( Sharma et al. 2019 , see also Fig. 13 ). Compared to the previous spectroscopic validation, this sample has almost no overlap with the training set and hence no SME parameters to compare to. We took the results from the binary pipeline, using only the photometric fit (Eq. ( 7 )), and compared them to the IRFM temperature values and reddening values from SFD (Schlegel, Finkbeiner, David) reddening maps ( Schlegel et al. 1998 ) and 3D reddening maps based on Pan-STARRS 1 photometry ( Green et al. 2018 ; hereafter the Bayestar maps). This comparison is shown in Fig. 3 , where we display results with and without the Gaia magnitudes in the photometric fit. We distinguish the Gaia magnitudes from other photometric passbands used in this work because their uncertainties are approximately an order of magnitude lower. They therefore affect the fit more strongly. Fig. 2 Comparison of SME and The Cannon labels for The Cannon validation sample. The Cannon values produced by the binary pipeline are subtracted from the SME values. Fig. 3 Comparison of T eff (orange) and E ( B − V ) (green) parameters as derived by the binary pipeline (using only the photometric fit) to the literature values (indicated on the horizontal axis). The literature values are subtracted from those given by the binary pipeline. The lighter shaded distributions correspond to results from the binary pipeline when the Gaia magnitudes are excluded from the fit. Figure 3 shows some important problems. The most striking is a bias towards higher temperatures as compared to both the GALAH DR2 values and those from the IRFM. An additional test that we performed using a larger validation sample (without the need for external information about the radii) also shows strong grid effects, which diminish considerably, however, when we exclude Gaia magnitudes. The grid effect has a spacing of about 250 K, and it might originate from the SED model in combinationwith small uncertainties of Gaia data. Excluding Gaia magnitudes from the fit
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