{"id":"W4413782260","doi":"10.1016/j.nuclcard.2025.102413","title":"Comprehensive and Large-Scale Analytical and Clinical Validation of an Artificial Intelligence-Based Tool for Volumetric Myocardial Blood Flow Parametric Mapping With 82Rb PET","year":2025,"lang":"en","type":"article","venue":"Journal of Nuclear Cardiology","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ottawa Hospital; University of Ottawa; Montreal Heart Institute; Micropharma (Canada)","funders":"","keywords":"Medicine; Scale (ratio); Parametric statistics; Blood flow; Medical physics; Nuclear medicine; Radiology; Cartography; Statistics","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":[0.009783182,0.000811649,0.0006682803,0.001044725,0.0005073001,0.001493896,0.001167619,0.001085227,0.001062298],"category_scores_gemma":[0.01090585,0.0003175757,0.0004231026,0.0006213336,0.001621113,0.00050896,0.001353561,0.0008067199,0.0005542944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003761695,"about_ca_system_score_gemma":0.001003806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001101144,"about_ca_topic_score_gemma":0.001315255,"domain_scores_codex":[0.996785,0.001515655,0.0002077256,0.0004799324,0.0008945605,0.0001171688],"domain_scores_gemma":[0.9954,0.002106637,0.0003388117,0.001017109,0.000995461,0.0001420741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004214307,0.004772055,0.07485308,0.0008141922,0.0009672904,0.001132463,0.001650625,0.04103075,0.5224313,0.00247603,0.004106628,0.3415512],"study_design_scores_gemma":[0.0008363432,0.00937271,0.2459267,0.0002048892,0.0009391855,0.005524198,0.0009111914,0.3932948,0.3214881,0.003768072,0.01746845,0.0002654279],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7782695,0.001240506,0.2144659,0.0003913446,0.00008592536,0.00115644,0.001140118,0.001014117,0.002236137],"genre_scores_gemma":[0.9046332,0.0003213059,0.09157231,0.0002320014,0.00003846256,0.0007083958,0.001388872,0.0001624953,0.0009429058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009783182,"threshold_uncertainty_score":0.05173904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04832777294683457,"score_gpt":0.3562150035592221,"score_spread":0.3078872306123875,"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."}}