{"id":"W1659685982","doi":"10.1186/1471-2105-16-s11-s1","title":"Highlights from the 5th Symposium on Biological Data Visualization: Part 1","year":2015,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; BC Cancer Agency","funders":"","keywords":"Visualization; Data science; Computer science; Data visualization; Process (computing); Creative visualization; Soundness; Data mining","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02101314,0.002579752,0.001916154,0.007013499,0.002890639,0.01347851,0.003796715,0.007159693,0.03804614],"category_scores_gemma":[0.03392306,0.001023237,0.003443717,0.003629197,0.001718914,0.006092784,0.005778066,0.009079025,0.02616744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004488664,"about_ca_system_score_gemma":0.01174709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001967691,"about_ca_topic_score_gemma":0.004382135,"domain_scores_codex":[0.9830045,0.003429795,0.001812689,0.001677547,0.008883083,0.001192414],"domain_scores_gemma":[0.9223691,0.00690084,0.003386969,0.001634899,0.05237771,0.01333045],"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":[0.00008170912,0.00003501743,0.0001843573,0.001541025,0.00003727646,0.0001550062,0.0001875763,0.00008093011,0.0009036129,0.001081618,0.9460265,0.04968534],"study_design_scores_gemma":[0.00001306253,0.00006095244,0.0003964508,0.001078101,0.00003183709,0.0001939403,0.0001364306,0.00006392544,0.0003841498,0.001077647,0.9965338,0.00002976233],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"review","genre_scores_codex":[0.0007923002,0.07335405,0.005372057,0.1161832,0.7858947,0.0006007794,0.000712806,0.0004530268,0.01663702],"genre_scores_gemma":[0.008266631,0.1429264,0.007912413,0.05211187,0.6776469,0.001329579,0.003145884,0.001265291,0.1053952],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.03804614,"threshold_uncertainty_score":0.1272771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1068324075757498,"score_gpt":0.2995042047459029,"score_spread":0.1926717971701531,"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."}}