  In the flourishing field of gravitational-wave astronomy, accurately
inferring binary black hole merger formation channels is paramount. The
Bayesian hierarchical model selection analysis offers a promising methodology
(see, e.g., One Channel to Rule Them All, Zevin et al. 2021). However,
recently, Cheng et al. (2023) highlighted a critical caveat: observed channels
absent in known models can bias branching fraction estimates. In this research
note, we introduce a test to detect missing channels in such analyses. Our
findings show a commendable success rate in identifying these elusive channels.
Yet, in scenarios where missing channels closely overlap with recognized ones,
discerning the difference remains challenging.
