{"id":"W3201828575","doi":"10.1016/j.cardfail.2021.08.003","title":"Risk Prediction in Cardiogenic Shock: Current State of Knowledge, Challenges and Opportunities","year":2021,"lang":"en","type":"review","venue":"Journal of Cardiac Failure","topic":"Mechanical Circulatory Support Devices","field":"Engineering","cited_by":61,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto General Hospital; University Health Network","funders":"","keywords":"Medicine; Cardiogenic shock; Intensive care medicine; Variety (cybernetics); Risk analysis (engineering); Psychological intervention; Shock (circulatory); Cardiology; Internal medicine; Artificial intelligence; Myocardial infarction; Computer science","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001226302,0.0003885067,0.00306199,0.0005006033,0.00001757633,0.00002321926,0.0001908299,0.0002228221,0.00001537487],"category_scores_gemma":[0.00007476294,0.0003362197,0.001156531,0.0001714599,0.00003493957,0.0001952646,0.00006728085,0.001054549,0.000003276637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000153016,"about_ca_system_score_gemma":0.0003336268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.236633e-7,"about_ca_topic_score_gemma":0.000007228657,"domain_scores_codex":[0.9971755,0.000522605,0.001475698,0.0002008446,0.0003884688,0.0002369544],"domain_scores_gemma":[0.9984054,0.0002216071,0.0006454267,0.0002948841,0.0002342958,0.0001983656],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001206193,0.00001643501,0.00003038937,0.01679773,0.001014084,0.00003060064,0.0002071311,0.0001040664,4.598068e-7,0.00002281188,0.0007979909,0.9809771],"study_design_scores_gemma":[0.0001130315,0.00003695867,0.0001665501,0.01320839,0.00159742,0.0001165178,0.0001070241,0.0000310765,0.000003493005,0.00004220974,0.9843407,0.000236622],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003299892,0.997208,0.00002575469,0.000005503745,0.001608198,0.0002297749,0.0002561376,0.00002154976,0.0003151182],"genre_scores_gemma":[0.001465406,0.9979601,0.00004918676,4.734116e-7,0.0004129555,0.00001412502,0.00002011525,0.00006577163,0.00001190295],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9835427,"threshold_uncertainty_score":0.999909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05378664898156323,"score_gpt":0.2844228377953325,"score_spread":0.2306361888137693,"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."}}