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tokens: is ∼92.5 per cent, and improves as the offset distance becomes closer to zero. Ching et al. ( 2017 ) provided optical identifications using data from Sloan Digital Sky Survey (SDSS) of 19 179 of radio sources from FIRST using over an area of 800 deg 2 . They obtain a reliability of 93.5 per cent using a rule-based methodology with visualization inspection of complex FIRST sources. We generalize this analysis to all collated groups and investigate any second-order effects as functions of collated number of FIRST components, maximum distance ( D ) and curliness ( Q ). The R was evaluated across a range of separations (spaced from 0 to 10 arcsec in steps of 1 arcsec) after dividing our collated groups into meaningful subsets. For the subsets in the D and Q dimensions, we established boundaries at the 20th, 40th, 60th, 80th, 85th, 90th, and 95th percentiles, where finer bins were used in regions of the parameter space with rapid variations identified after inspection of the distribution. Otherwise, we created boundaries based on the number of associated FIRST components in each collated group. We interpolate between R measures across these dimensions to create a set of reliability curves, which we present as in Fig. 5 . Broadly speaking, these curves show that as measures of complexity increase, judged either by the number of collated FIRST components or Q , the infrared predicted position becomes less reliable. At a threshold of 3.4 arcsec, these R are above 80 per cent with significant spreads of upwards of ∼12 per cent between the simple and complex groups. However, the reliability curves in Fig. 5(c) suggest groups across all D have about the same degree of reliability. We use these interpolated reliability curves to provide a measure of reliability for all collated groups in our catalogue data products for each of these dimensions. For groups outside the range of these reliability curves, we set the R = 0.5 across all dimensions. Of the 24 reliability curves in Fig. 5 , 6 have fewer than 20 genuine matches with separations 1 arcsec and are the most susceptible to small number statistical effects. Since increasing separations accumulate counts from smaller separations (i.e. bins are not exclusive), the number of genuine matches very quickly grows so that all other curves and separation bins have at least 20 genuine matches. Figure 5. Panel (a): the reliability curves of the cross-matched infrared predicted positions against AllWISE as a function of number of collated FIRST components. Panel (b): the reliability curves of the cross-matched infrared predicted positions made against AllWISE as a function of the parameter. Boundaries of the were spaced to contain roughly the same number of groups to maximize the clarity of the different reliability trends. All groups included in this figure contain three or more FIRST components. Panel (c): the same as panel (b) except as a function of D . All groups included in this figure contain two or