<p>Hyperparameter config.</p>

As the cornerstone of microbial research, metagenomics relies on the precise analysis of large-scale, multi-source genomic data. However, discriminating among diverse sequence types remains a formidable challenge.

To address this, we present CamFi (Codon-aware Multi-scale Feature Fusion), a unified framework integrating overlapping nucleotide-triplet representations with multi-scale dilated convolutions for classifying prokaryotic chromosomes, eukaryotic chromosomes, plasmids, and viruses. Benchmark evaluations demonstrate strong mean F1 scores of 97.70% for eukaryotic chromosomes and 94.13% for plasmids. On the CAMI II marine dataset, CamFi achieved a weighted F1 of 82.65%, ranking second among six methods based on reported aggregate metrics.