{"id":"W4388410058","doi":"10.1093/nar/gkad964","title":"IMG/PR: a database of plasmids from genomes and metagenomes with rich annotations and metadata","year":2023,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Nuclear Security Administration; Office of Science; Medical Research Council; Joint Genome Institute; U.S. Department of Energy","keywords":"Plasmid; Biology; Metadata; Horizontal gene transfer; Genome; Database; Genetics; Mobile genetic elements; Gene; Computational biology; World Wide Web; Computer science","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":[0.002488321,0.003369606,0.003301087,0.01170518,0.001638656,0.004361918,0.004850116,0.002778642,0.02090451],"category_scores_gemma":[0.008342758,0.002241381,0.001602769,0.01926975,0.000714548,0.005418217,0.005345261,0.0025933,0.028696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001522644,"about_ca_system_score_gemma":0.00528669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005147107,"about_ca_topic_score_gemma":0.006324189,"domain_scores_codex":[0.9982381,0.0002325537,0.0003140695,0.0004481279,0.0005432459,0.0002239029],"domain_scores_gemma":[0.9967443,0.0006741559,0.0007325252,0.0008737756,0.0004112966,0.0005640271],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002653939,0.0005265669,0.01152003,0.01659806,0.0006949143,0.001400763,0.00127315,0.005619868,0.08942451,0.0180908,0.629306,0.2228915],"study_design_scores_gemma":[0.0003790579,0.0001697023,0.007167778,0.0008193868,0.0003014675,0.0007781903,0.0003119312,0.003469856,0.01932373,0.009259699,0.9578056,0.0002136349],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00666591,0.003916689,0.03557134,0.0004779932,0.0001745518,0.0002551184,0.8739433,0.06971192,0.00928322],"genre_scores_gemma":[0.007005694,0.001766436,0.04519681,0.0001687889,0.00004047096,0.0002747915,0.9397728,0.004696494,0.00107761],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02090451,"threshold_uncertainty_score":0.06993258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05222245131801095,"score_gpt":0.3254994627776809,"score_spread":0.27327701145967,"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."}}