{"id":"W4394742381","doi":"10.1186/s44156-024-00043-2","title":"Validation of machine learning models for estimation of left ventricular ejection fraction on point-of-care ultrasound: insights on features that impact performance","year":2024,"lang":"en","type":"article","venue":"Echo Research and Practice","topic":"Ultrasound in Clinical Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; British Columbia Centre on Substance Use; Providence Health Care","funders":"Canadian Institutes of Health Research; Vancouver Coastal Health Research Institute","keywords":"Ejection fraction; Medicine; Intraclass correlation; Ultrasound; Cardiology; Point of care ultrasound; Internal medicine; Nuclear medicine; Heart failure; Radiology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.04243166,0.001817993,0.001281987,0.002089242,0.0005902894,0.002263322,0.001430858,0.001863191,0.0009450403],"category_scores_gemma":[0.0875558,0.0004330695,0.001502199,0.0008694664,0.001014687,0.001680934,0.001728547,0.001890357,0.0006224141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001687919,"about_ca_system_score_gemma":0.001747525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007802813,"about_ca_topic_score_gemma":0.003935874,"domain_scores_codex":[0.9861034,0.009057435,0.001040783,0.001941265,0.001321749,0.0005353627],"domain_scores_gemma":[0.8925929,0.09089316,0.004724674,0.004713337,0.006103911,0.000971959],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.002591244,0.001216965,0.3435465,0.0003927331,0.001634057,0.0002036604,0.0005110061,0.5283858,0.003278216,0.001078768,0.002570349,0.1145908],"study_design_scores_gemma":[0.0000545711,0.0005272653,0.02501125,0.00006810117,0.00007510299,0.00006274437,0.0000978398,0.9712714,0.001692302,0.0008532999,0.0002489634,0.00003711385],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8897528,0.001364705,0.1041919,0.0006499204,0.0001254171,0.0004233507,0.0009908931,0.0007934855,0.001707537],"genre_scores_gemma":[0.982569,0.0000937901,0.01577611,0.0001066171,0.00002422325,0.0001613252,0.00100766,0.00004619921,0.0002150856],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04243166,"threshold_uncertainty_score":0.2244028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1001773924186308,"score_gpt":0.4485504289664912,"score_spread":0.3483730365478603,"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."}}