We used Guppy for basecalling, which is neural network based and used to turn raw signal data into the predicted bases. There're no guarantees of accuracy, only tools to determine and assess quality. One major way of assessing accuracy is to compare the subject genome with other similar reference genomes and denote the high-degree of homology in highly-conserved regions.

There are quality checks throughout the entire process, starting from the raw read quality scores returned directly from the sequencer all the way to fully assembled genome completeness. In our paper, one of the tools we used for this is called BUSCO[0] which scored our assembly at 97.9%, a relatively high score for de novo assemblies.

[0] https://pubmed.ncbi.nlm.nih.gov/31020564/

You don't, not without either resequencing it with another sequencing system or benchmarking the sequencer with a known sequence.

Thanks man!