{"id":"W2147898530","doi":"10.1002/sim.3078","title":"CoPlot: A tool for visualizing multivariate data in medicine","year":2007,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Multivariate statistics; Multidimensional scaling; Computer science; Multivariate analysis; Data mining; Set (abstract data type); Data science; Data visualization; Data set; Visualization; Interpretation (philosophy); Artificial intelligence; Machine learning","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":[0.01312561,0.003079948,0.002813861,0.01361415,0.001558102,0.00646134,0.002367946,0.001881379,0.04441354],"category_scores_gemma":[0.06383004,0.001401697,0.002891292,0.01298357,0.001147655,0.007194898,0.00519932,0.004277122,0.007227092],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001006894,"about_ca_system_score_gemma":0.003134103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003452172,"about_ca_topic_score_gemma":0.003237642,"domain_scores_codex":[0.9916849,0.004755785,0.001059533,0.0007806713,0.001460345,0.0002586911],"domain_scores_gemma":[0.9446387,0.04341402,0.003283358,0.00352475,0.004156273,0.0009828764],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001480197,0.0003197022,0.008275038,0.005610993,0.001187008,0.001245244,0.004893789,0.02020017,0.005526204,0.06749164,0.3902919,0.4934781],"study_design_scores_gemma":[0.0006667672,0.0005785041,0.01431258,0.001975022,0.0005021325,0.00234219,0.002092543,0.1890713,0.009787436,0.2092309,0.5685023,0.0009382993],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004934779,0.001625483,0.9087839,0.001973515,0.0007573238,0.0005502168,0.01826752,0.05785306,0.005254258],"genre_scores_gemma":[0.04592622,0.001677447,0.9298602,0.0006161123,0.0004596745,0.002065551,0.009858515,0.007555193,0.001981146],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04441354,"threshold_uncertainty_score":0.1485781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04385822664028715,"score_gpt":0.3928479670720673,"score_spread":0.3489897404317801,"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."}}