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Table 1.

Performance statistics for Zoobot and GALFIT.

RMSE RAE ⟨ΔfAGN Outlier (20%) Outlier (30%)
Zoobot 0.013 ± 0.005 0.076 ± 0.005 −0.0018 ± 0.0002 0.065 ± 0.004 0.061 ± 0.003
ZoobotM 0.014 ± 0.006 0.102 ± 0.009 −0.0017 ± 0.0005 0.072 ± 0.010 0.065 ± 0.010
ZoobotNM 0.013 ± 0.006 0.073 ± 0.005 −0.0018 ± 0.0002 0.065 ± 0.004 0.061 ± 0.004
GALFIT (fhost from original image) 0.12 ± 0.07 0.19 ± 0.01 −0.018 ± 0.002 0.19 ± 0.01 0.13 ± 0.01
GALFITM (fhost from original image) 0.13 ± 0.07 0.27 ± 0.05 −0.024 ± 0.004 0.25 ± 0.03 0.18 ± 0.02
GALFITNM (fhost from original image) 0.12 ± 0.07 0.17 ± 0.01 −0.016 ± 0.002 0.16 ± 0.01 0.11 ± 0.01
GALFIT (fhost from model) 0.17 ± 0.08 0.51 ± 0.02 −0.075 ± 0.003 0.46 ± 0.01 0.35 ± 0.01
GALFITM (fhost from model) 0.16 ± 0.09 0.48 ± 0.07 −0.087 ± 0.007 0.54 ± 0.04 0.39 ± 0.04
GALFITNM (fhost from model) 0.17 ± 0.08 0.52 ± 0.02 −0.073 ± 0.003 0.45 ± 0.02 0.34 ± 0.01

Notes. We summarise the overall performance from Zoobot and GALFIT (for both ways of calculating the AGN contribution fraction), in terms of the RMSE, RAE, mean difference, and outlier fractions (at different percentage levels, 20% and 30%). We show the results for the whole sample and mergers (M) and non-mergers (NM) separately.

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