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Table A.3.

Feature ranking based on the three cluster labels.

ID Feature Description
1 amp_G* Amplitude of variability in the G band (mag.)
2 range_mag_g_fov The range of the G-band time series
3 iqr_mag_g_fov The Interquartile Range (IQR) of the G-band time series
4 log_sigvar* Significance of variability in the G band in a log scale
5 stetson_mag_g_fov Stetson G FoV variability index
6 n05* Number of peaks above 0.5 of the normalised Ψ periodogram based on the G band
7 std_dev_over_rms_err_mag_g_fov S/N ratio G FoV estimate
8 p95_100* 95th percentile of the first 100 frequency peaks based on the G-band lightcurves
9 mad_mag_g_fov The Median Absolute Deviation (MAD) of the G-band time series
10 bp_rp ∤ BP − RP colour
11 outlier_median_g_fov The most outlying measurement with respect to the median
12 p99* 99th percentile of all periodogram peaks based on the G-band lightcurves
13 amp_BP* Amplitude of variability in the BP band(mag.)
14 Period_G* Derived period from the G-band lightcurve
15 abbe_mag_g_fov The Abbe value of the G-band time series
16 kurtosisG* G-band kurtosis of the periodogram
17 skewness_mag_bp The standardised unbiased unweighted skewness of the BP-band time series
18 abbe_mag_bp The Abbe value of the BP-band time series
19 psi_sigvar* G-band median absolute deviation of the periodogram
20 abbe_mag_rp The Abbe value of the RP-band time series
21 fapG* False alarm probability of the Lomb-Scargle dominant frequency peak (G band)
22 Period_RP* Derived period from the RP-band lightcurve
23 Period_BP* Derived period from the BP-band lightcurve
24 frac_period* Period over the standard deviation (std) of the three band Gaia lightcurve periods
25 std* Standard deviation of the G, BP, and RP periods
26 fapRP* False alarm probability of the Lomb-Scargle dominant frequency peak (RP band)
27 fapBP* False alarm probability of the Lomb-Scargle dominant frequency peak (BP band)

Notes. Features marked with (*) were computed in this work, those with (∤) are from the Gaia DR3 source database (Gaia Collaboration 2023), while the rest were obtained from the Gaia variability summary table (Eyer et al. 2023).

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