{"id":"W2293541784","doi":"10.1109/biovis.2011.6094039","title":"Challenges session","year":2011,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency","funders":"","keywords":"Visualization; Session (web analytics); Computer science; Presentation (obstetrics); Data visualization; Cover (algebra); Information visualization; Data science; World Wide Web; Multimedia; Artificial intelligence; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005496609,0.00002433316,0.0000250864,0.00002366382,0.00001796239,0.00001665543,0.000266821,0.00001091217,0.0001322509],"category_scores_gemma":[0.000005763206,0.0000177488,0.000008932439,0.00006266782,0.000004986727,0.0002267961,0.00009208968,0.000012299,0.0002179699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001711873,"about_ca_system_score_gemma":0.000006096396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002884318,"about_ca_topic_score_gemma":0.000003199448,"domain_scores_codex":[0.9997519,0.000008837967,0.00004202056,0.00008954769,0.00005657692,0.00005114371],"domain_scores_gemma":[0.9997395,0.000004000994,0.00001108891,0.000199768,0.00001628164,0.00002934261],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[9.850692e-8,0.00001980165,0.00004856286,0.000001287462,9.421703e-7,0.000001179367,0.0003328861,6.816619e-8,0.00001189788,0.9457319,0.001572221,0.05227916],"study_design_scores_gemma":[0.0008420215,0.0002801371,0.03904119,0.00006152265,0.00001036761,0.00003344689,0.0009318566,0.3243023,0.03042025,0.1205779,0.4825967,0.0009023243],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00004948165,0.00003865142,0.6651434,0.0002396924,0.00006261197,0.000008658306,8.637399e-8,0.0001064427,0.3343509],"genre_scores_gemma":[0.8822735,0.0004173919,0.1107053,0.001356173,0.00003138797,0.000001390912,0.000001946026,0.000004349119,0.005208562],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.882224,"threshold_uncertainty_score":0.2801635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1493187077325498,"score_gpt":0.3284194477397812,"score_spread":0.1791007400072314,"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."}}