{"id":"W7118474821","doi":"10.1097/ccm.0000000000006970","title":"Predicting Mortality in Cardiogenic Shock—Human or Machine?","year":2025,"lang":"en","type":"article","venue":"Critical Care Medicine","topic":"Mechanical Circulatory Support Devices","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University; Lakeridge Health; University of Ottawa","funders":"","keywords":"Cardiogenic shock; MEDLINE; Mortality rate; Risk assessment","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":[0.002280991,0.0005446193,0.0004597751,0.001188325,0.0001601669,0.001255903,0.0005073205,0.0008518744,0.0022639],"category_scores_gemma":[0.01019029,0.0001365923,0.0004418296,0.0004811587,0.0005017469,0.001082749,0.0004280211,0.0006271675,0.0005895419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000143709,"about_ca_system_score_gemma":0.0003032514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004026441,"about_ca_topic_score_gemma":0.0006525264,"domain_scores_codex":[0.9993318,0.0004202242,0.00005512846,0.00005928206,0.00007911449,0.00005443052],"domain_scores_gemma":[0.9948719,0.002979615,0.0008993984,0.0003914547,0.0003808525,0.0004767562],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004784733,0.0001128371,0.9619674,0.00004742043,0.0001293091,0.00009000429,0.0001087022,0.001283293,0.0003968484,0.0002775894,0.001214959,0.03389306],"study_design_scores_gemma":[0.0000743425,0.002071031,0.9479399,0.0003017641,0.0003784912,0.0008389071,0.00103803,0.03608162,0.001378006,0.005269482,0.004559971,0.0000684199],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9846274,0.002321885,0.00630864,0.0018326,0.0003493811,0.00002767797,0.000425577,0.00009015048,0.004016624],"genre_scores_gemma":[0.9973157,0.0005710769,0.001196359,0.0001778697,0.0002399388,0.00001032809,0.0001928989,0.000008079392,0.0002877786],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002280991,"threshold_uncertainty_score":0.01206321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02745307183881129,"score_gpt":0.3270417990386363,"score_spread":0.299588727199825,"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."}}