{"id":"W2139249401","doi":"10.1093/bioinformatics/btt673","title":"The International Society of Computational Biology presents: the Great Lakes Bioinformatics Conference, May 16–18, 2014, Cincinnati, Ohio","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":"","keywords":"Data science; Computational biology; Bioinformatics; Library science; Biology; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01208259,0.002334599,0.001712734,0.002102112,0.002468132,0.01075314,0.002658576,0.00325144,0.2222697],"category_scores_gemma":[0.01693419,0.0009995569,0.001244595,0.001940382,0.001491058,0.005924323,0.006279881,0.007073973,0.1212242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0023426,"about_ca_system_score_gemma":0.005479896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00353407,"about_ca_topic_score_gemma":0.005423938,"domain_scores_codex":[0.9945019,0.001302449,0.0003398853,0.001288193,0.002109144,0.0004582911],"domain_scores_gemma":[0.9876067,0.001894263,0.0003819045,0.001185669,0.004773885,0.004157481],"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":[0.00003722862,0.00002126842,0.0002188035,0.00007288859,0.00001228443,0.0000262855,0.00004356919,0.00009242036,0.0002287038,0.001077902,0.95864,0.03952861],"study_design_scores_gemma":[0.00001728922,0.0000155879,0.0005174651,0.000128295,0.00000867058,0.00003587883,0.00009656383,0.0003859205,0.0001560961,0.001196995,0.9974245,0.00001683667],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.005378439,0.06647336,0.0622821,0.3161809,0.2184771,0.001220187,0.01835439,0.01612828,0.2955051],"genre_scores_gemma":[0.01337786,0.04935132,0.04104403,0.03199929,0.03318831,0.001602715,0.0240779,0.007807979,0.7975506],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2222697,"threshold_uncertainty_score":0.7435662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02553924280974949,"score_gpt":0.2896759633183911,"score_spread":0.2641367205086416,"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."}}