{"id":"W4408391722","doi":"10.1038/s41746-025-01526-0","title":"Holistic AI analysis of hybrid cardiac perfusion images for mortality prediction","year":2025,"lang":"en","type":"article","venue":"npj Digital Medicine","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; University of Calgary","funders":"National Heart, Lung, and Blood Institute","keywords":"Myocardial perfusion imaging; Medicine; Perfusion; Receiver operating characteristic; Confidence interval; Correction for attenuation; Internal medicine; Radiology; Cardiology; Nuclear medicine; Positron emission tomography","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":[],"consensus_categories":[],"category_scores_codex":[0.0003099031,0.0001663516,0.0008730695,0.0005681751,0.00005074017,0.00002208856,0.00006234797,0.00004650037,0.00003068228],"category_scores_gemma":[0.003533024,0.0001334044,0.0003971375,0.0008551186,0.0002425582,0.0001140805,0.0000411368,0.0001267152,0.0000024612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007284179,"about_ca_system_score_gemma":0.0001040457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008443677,"about_ca_topic_score_gemma":7.98588e-7,"domain_scores_codex":[0.9986134,0.00001736138,0.0004672699,0.0003063301,0.000389545,0.0002061187],"domain_scores_gemma":[0.9983205,0.0005401702,0.00009631206,0.0004382358,0.0004784038,0.0001263475],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002193958,0.000234715,0.8939954,0.0004361458,0.002306499,0.00002124776,0.00009876655,0.0001172223,0.002866906,0.0004648121,0.07056925,0.02866963],"study_design_scores_gemma":[0.00192673,0.0003687659,0.9663164,0.0005797747,0.014737,0.000005933418,0.000247658,0.002784122,0.00279193,0.0005800854,0.009532874,0.0001287314],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9070283,0.003498018,0.0357013,0.003453375,0.001720231,0.0009769941,0.002625937,0.0001866573,0.04480926],"genre_scores_gemma":[0.9966666,0.00009700184,0.00005583839,0.0005172102,0.0003304852,0.00003474182,0.001233011,0.00001345803,0.001051622],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0896384,"threshold_uncertainty_score":0.5440072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01980106439044877,"score_gpt":0.3370345495886497,"score_spread":0.3172334851982009,"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."}}