{"id":"W4396940192","doi":"10.1093/bib/bbae229","title":"AnnoView enables large-scale analysis, comparison, and visualization of microbial gene neighborhoods","year":2024,"lang":"en","type":"article","venue":"Briefings in Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Genome; Visualization; Upload; Genome browser; Interactive visualization; Computational biology; Bacterial genome size; Gene Annotation; Annotation; Biology; KEGG; Computer science; Gene; Genomics; Data mining; Genetics; World Wide Web; Gene ontology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002768081,0.0001196966,0.0002448505,0.000127917,0.0000399618,0.00004391079,0.0001427947,0.00009206872,0.000003883315],"category_scores_gemma":[0.0000294513,0.0001134267,0.00005350674,0.0003628983,0.00006264247,0.000003595286,0.0002502866,0.00004256358,0.000001114793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006279964,"about_ca_system_score_gemma":0.00004562655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003970895,"about_ca_topic_score_gemma":0.0001445864,"domain_scores_codex":[0.9991005,0.00001637047,0.0004573982,0.0001805869,0.0000779499,0.0001671586],"domain_scores_gemma":[0.9995575,0.00001423331,0.0000962401,0.0002499853,0.00005178954,0.00003027357],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001580228,0.0006489977,0.3886167,0.004190893,0.004292828,0.000007701595,0.01840742,0.004175891,0.5120983,0.005065144,0.02517609,0.0371621],"study_design_scores_gemma":[0.001931052,0.0005313626,0.09925009,0.0003018294,0.001358537,0.00004481214,0.001920638,0.457052,0.1413559,0.0004763012,0.2944824,0.001295109],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9380034,0.02088509,0.0397905,0.0001458045,0.0001247333,0.0001986719,0.0002487355,0.000009136737,0.0005938752],"genre_scores_gemma":[0.9866131,0.0028073,0.009899835,0.000241309,0.00004838027,0.000003390165,0.0003408168,0.00001149034,0.00003439403],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4528761,"threshold_uncertainty_score":0.4625406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00832843084101445,"score_gpt":0.2627670856006795,"score_spread":0.2544386547596651,"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."}}