{"id":"W2913101658","doi":"10.1109/dsaa.2018.00027","title":"Cohort Representation and Exploration","year":2018,"lang":"en","type":"article","venue":"","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Representation (politics); Cohort; Trajectory; Similarity (geometry); Data mining; Machine learning; Artificial intelligence; Information retrieval; Statistics; Mathematics","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":[0.002615949,0.0007656888,0.0008579048,0.003322971,0.0006828731,0.002485539,0.001729251,0.001090468,0.004719923],"category_scores_gemma":[0.015531,0.0004348607,0.001970946,0.00286788,0.0008081406,0.003281773,0.00422889,0.001335746,0.0006201681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00102565,"about_ca_system_score_gemma":0.002092418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005366265,"about_ca_topic_score_gemma":0.005606173,"domain_scores_codex":[0.9984194,0.0005720416,0.000131165,0.0004385138,0.0002953415,0.0001436101],"domain_scores_gemma":[0.9950571,0.003217301,0.000390747,0.0008093626,0.0003569669,0.0001686133],"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":[0.000451279,0.000173816,0.02244621,0.0005766031,0.0002290853,0.0004607571,0.001434462,0.3153886,0.003170335,0.182632,0.01836619,0.4546708],"study_design_scores_gemma":[0.00003911587,0.00009571137,0.001636236,0.0001333597,0.0000501086,0.0002916078,0.0004204216,0.7605175,0.001611536,0.2189696,0.01620023,0.00003464192],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02438586,0.0007009216,0.9680679,0.00105849,0.00006368378,0.0001929337,0.002404803,0.001005139,0.002120217],"genre_scores_gemma":[0.2924988,0.0009698176,0.6958829,0.0003907371,0.0001062818,0.0006388699,0.00684393,0.000226629,0.002442152],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005366265,"threshold_uncertainty_score":0.01578969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04059641533738914,"score_gpt":0.3446512238114328,"score_spread":0.3040548084740436,"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."}}