{"id":"W4413619423","doi":"10.1101/2025.08.21.671630","title":"Accurate hybrid plasmids assembly with HyPlAs","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Plasmid; Computer science; Computational biology; Biology; Genetics; Gene","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001533563,0.00140794,0.0009748237,0.001143467,0.0006913451,0.002081,0.001365652,0.0007407065,0.01028928],"category_scores_gemma":[0.00420409,0.000926836,0.001122246,0.0008687418,0.0004808453,0.001458858,0.002541335,0.001956242,0.0121346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004373638,"about_ca_system_score_gemma":0.0007482658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009169552,"about_ca_topic_score_gemma":0.001545976,"domain_scores_codex":[0.9987525,0.0001960149,0.00008491025,0.0004159904,0.0004455616,0.0001051141],"domain_scores_gemma":[0.9978814,0.000670394,0.0001927414,0.000748129,0.0003501471,0.0001573123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001471174,0.0002042151,0.005628184,0.001843028,0.0004280543,0.0007388068,0.0007877202,0.03994718,0.4812114,0.01759101,0.1392519,0.3108974],"study_design_scores_gemma":[0.0001340246,0.0002290551,0.003070361,0.0001648497,0.00009230417,0.0006420992,0.0002705865,0.2355765,0.5561781,0.0185658,0.1848377,0.0002387646],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0454174,0.0007252168,0.7786399,0.0005018864,0.0004074485,0.0002068278,0.01819728,0.1497631,0.00614082],"genre_scores_gemma":[0.153791,0.000464668,0.7770676,0.0003288549,0.00009453615,0.0005061547,0.04625819,0.01434691,0.007142155],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01028928,"threshold_uncertainty_score":0.03442109,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01233467175349878,"score_gpt":0.2079437164269075,"score_spread":0.1956090446734087,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}