{"id":"W6889064195","doi":"10.25384/sage.c.4698446","title":"Comparative Prognostic Accuracy of Risk Prediction Models for Cardiogenic Shock","year":2019,"lang":"en","type":"other","venue":"Sage Journals Data","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cardiogenic shock; Receiver operating characteristic; Confidence interval; Population; Framingham Risk Score; Risk assessment; Risk stratification","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":[0.01430066,0.001521584,0.0007776212,0.002623246,0.0003764234,0.001889434,0.001021851,0.0007985656,0.00117379],"category_scores_gemma":[0.0394263,0.0003150666,0.001045782,0.001092878,0.0006168681,0.0007632421,0.0009854152,0.0009451814,0.0004731427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001055703,"about_ca_system_score_gemma":0.001349436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01006859,"about_ca_topic_score_gemma":0.006096406,"domain_scores_codex":[0.9963455,0.001930922,0.0002689401,0.0004624181,0.0007404872,0.0002518835],"domain_scores_gemma":[0.9711071,0.02265433,0.001918565,0.001093407,0.002425804,0.0008006867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00225531,0.0001751196,0.9190296,0.0001002528,0.001020546,0.0001263221,0.0002319901,0.02856965,0.0003171991,0.000320394,0.001499276,0.04635436],"study_design_scores_gemma":[0.0002230394,0.001197639,0.4128121,0.0002042329,0.001062217,0.0004498285,0.0004608654,0.5786171,0.001080376,0.002516109,0.001281899,0.00009461445],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9825661,0.001773455,0.01153374,0.0006485533,0.0001392333,0.00007347704,0.0008514935,0.0003551805,0.002058843],"genre_scores_gemma":[0.9974858,0.0001926452,0.001422776,0.00002502798,0.0000278709,0.00001392597,0.0006753333,0.00001364579,0.0001430555],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.01430066,"threshold_uncertainty_score":0.07563001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1254324350810693,"score_gpt":0.3647452687550569,"score_spread":0.2393128336739876,"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."}}