{"id":"W1979164183","doi":"10.1002/cfg.215","title":"Meeting review: Intelligent Systems for Molecular Biology 2002 (ISMB02)","year":2002,"lang":"en","type":"article","venue":"Comparative and Functional Genomics","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Library science; Art history; Environmental ethics; Data science; Computational biology; History; Biology; Philosophy","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":[0.000292133,0.0001566554,0.0002338886,0.00004584427,0.0001230068,0.0000287127,0.000115632,0.0001143524,0.0000601841],"category_scores_gemma":[0.0001109171,0.0001345874,0.00008806198,0.00005976151,0.000182309,0.000003175143,0.0001018073,0.00008640088,0.00005178012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000215382,"about_ca_system_score_gemma":0.00003547802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005004985,"about_ca_topic_score_gemma":0.000002721784,"domain_scores_codex":[0.9989513,0.00005206557,0.0003366332,0.0002749687,0.0001175482,0.000267543],"domain_scores_gemma":[0.9993104,0.00004742321,0.00009581145,0.0001741463,0.000227954,0.0001442648],"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":[0.0002703858,0.0003944062,0.0005475412,0.001537204,0.0007240682,0.000002376673,0.0003971584,0.001039977,0.4054354,0.004810772,0.5691645,0.01567622],"study_design_scores_gemma":[0.0004211153,0.0005359905,0.00007248468,0.00007462824,0.00003298876,0.00001730779,0.0001844671,0.01018717,0.01177434,0.0001719716,0.9762864,0.0002411755],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.09900008,0.5213138,0.3577909,0.001465489,0.001550274,0.002527741,0.0003469058,0.00003263886,0.01597214],"genre_scores_gemma":[0.7324183,0.2362421,0.008706204,0.005275509,0.00206193,0.0005026996,0.001499269,0.00006778165,0.01322622],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6334182,"threshold_uncertainty_score":0.5488313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07821087889069372,"score_gpt":0.3214664407219208,"score_spread":0.243255561831227,"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."}}