In this work, we present a framework that explores the tradeoff between the undetected error rate (UER) and block error rate (BLER) of polar-like codes. It relies on a novel approximation for what we call codebook probability, which assumes an auxiliary distribution mimicking the dynamics of decoding algorithms with successive cancellation (SC) decoding schedule. Simulation results demonstrates that, in the case of SC list decoding, the proposed framework outperforms the state-of-art approximations of Forney's generalized decoding rule for polar-like codes with dynamic frozen bits. In addition, the proposed generalized decoding outperforms the CRC-concatenated polar codes significantly in both BLER and UER. Finally, we briefly discuss two potential applications of the approximated codebook probability: coded pilot-free channel estimation and bitwise soft-output decoding.