Consistency check on in-distribution testing. Left: Trained ensemble of three clustering NNs and combined PDF of log(σ_DM/m) for the known BAHAMAS-0, BAHAMAS-0.3, and BAHAMAS-1 (solid blue shades) and unknown BAHAMAS-0.1 (dashed black). We find a cross-section of ∼0.05 cm² g⁻¹ and within 1σ of 0.1 cm² g⁻¹ for BAHAMAS-0.1. Right: Projected 7D latent space from our clustering algorithm into a 1D distance PDF, where each known simulation (blue shades) is projected in the direction from the centre of their distribution to the centre of BAHAMAS-0.1. BAHAMAS-0.1 (hatched black) is projected in the direction of BAHAMAS-0.3 to show the greatest overlap. The distance has arbitrary units as it depends on the scale of the latent space. BAHAMAS-0.1 shares a large overlap of 49% and 55% with BAHAMAS-0 and BAHAMAS-0.3, respectively, leading to the conclusion that it lies within the training domain.