{"id":"W2945501761","doi":"10.1093/bioinformatics/btz413","title":"HyAsP, a greedy tool for plasmids identification","year":2019,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Contig; Plasmid; Computer science; Genome; Greedy algorithm; Identification (biology); Computational biology; Biology; Genetics; Gene; Algorithm","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":[0.0001312218,0.00009610195,0.00009311569,0.00002465759,0.00005484691,0.00002787148,0.0001301355,0.00007504328,0.000007734375],"category_scores_gemma":[0.00003703019,0.00008913391,0.00007253826,0.00003508573,0.00002276693,0.000001484523,0.00006450902,0.00002238818,0.00009058122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000747466,"about_ca_system_score_gemma":0.00003215094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001243813,"about_ca_topic_score_gemma":0.000002151202,"domain_scores_codex":[0.9994157,0.000004610754,0.0002434137,0.0001108626,0.00006975638,0.0001556626],"domain_scores_gemma":[0.9995199,0.00001129521,0.00009405788,0.0002719692,0.00007721686,0.00002558721],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001542882,0.00008090297,0.01821129,0.0003916822,0.00024517,1.547911e-7,0.0006115061,0.0004426874,0.9338547,0.002721114,0.01990259,0.02338389],"study_design_scores_gemma":[0.002916115,0.001125347,0.04190322,0.00002844802,0.00008554039,0.0000190274,0.000890454,0.01833075,0.2717486,0.0009254462,0.6610654,0.0009616135],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917595,0.0001405549,0.0051475,0.00005826094,0.000375879,0.0004838743,0.000074683,0.000005254497,0.001954477],"genre_scores_gemma":[0.9881567,0.00008350662,0.009333055,0.0002197416,0.0001175217,0.00004594367,0.000129161,0.00001315795,0.001901179],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6621061,"threshold_uncertainty_score":0.3634775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01003540163125125,"score_gpt":0.2286035975719128,"score_spread":0.2185681959406616,"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."}}