{"id":"W2152852962","doi":"10.1093/bioinformatics/btt630","title":"ISCB/SPRINGER series in computational biology","year":2013,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institutes of Health","keywords":"Computer science; Computational genomics; Publication; Systems biology; Data science; Computational biology; Genomics; Biology; Genome; Genetics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002495576,0.0001670215,0.0001682806,0.0001410151,0.00006303647,0.00006817617,0.0002997798,0.0002203168,0.0001458935],"category_scores_gemma":[0.0001993407,0.0001398336,0.00006548323,0.0001493557,0.0002525719,0.00002481232,0.0002357127,0.0001353742,0.0005244015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000213875,"about_ca_system_score_gemma":0.0001248378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003416665,"about_ca_topic_score_gemma":0.00002651055,"domain_scores_codex":[0.9986404,0.00002836381,0.0005339335,0.0001415512,0.0002190542,0.0004367537],"domain_scores_gemma":[0.9993025,0.00002267896,0.00009555897,0.0002642636,0.0001548642,0.0001601234],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004162483,0.001303353,0.1404325,0.002045447,0.0005882495,0.00001463847,0.005876604,0.003348148,0.09610987,0.01533033,0.2044308,0.5301037],"study_design_scores_gemma":[0.006964453,0.00363134,0.1670177,0.0002000145,0.00003595999,0.0001797303,0.005928616,0.1475075,0.04502369,0.01876462,0.6018241,0.002922306],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9335003,0.0004275209,0.03112871,0.00278876,0.0006790083,0.001263587,0.00008860375,0.00006542229,0.03005802],"genre_scores_gemma":[0.9331433,0.0003918047,0.06311435,0.001145856,0.0002124875,0.00006543666,0.0005546489,0.00002198192,0.001350187],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5271814,"threshold_uncertainty_score":0.6740295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01531003054439102,"score_gpt":0.2721442721398233,"score_spread":0.2568342415954323,"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."}}