{"id":"W2097614843","doi":"10.5267/j.esm.2014.2.002","title":"Numerical method to measure velocity integration, stroke volume and cardiac output while rest: using 2D fluid-solid interaction model","year":2014,"lang":"en","type":"article","venue":"Engineering Solid Mechanics","topic":"Cardiovascular Function and Risk Factors","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Rest (music); Measure (data warehouse); Stroke volume; Materials science; Volume (thermodynamics); Mechanics; Stroke (engine); Cardiac output; Mechanical engineering; Computer science; Physics; Acoustics; Internal medicine; Medicine; Hemodynamics; Engineering; Thermodynamics; Heart rate; Blood pressure; Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008069675,0.0002605717,0.000573711,0.0002282397,0.0000959946,0.00005078596,0.00006346471,0.0001897166,0.0000107434],"category_scores_gemma":[0.0004832225,0.0002490625,0.0002797485,0.0002327685,0.000005487195,0.0001295276,0.0000516058,0.0004191161,0.00001644943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002499484,"about_ca_system_score_gemma":0.00006452946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005656039,"about_ca_topic_score_gemma":0.000001702872,"domain_scores_codex":[0.9985129,0.00008501446,0.0003155274,0.0003909448,0.0003969985,0.0002986621],"domain_scores_gemma":[0.9989761,0.00004590209,0.00005322214,0.0003804853,0.0002225632,0.0003217463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001030394,0.00004418274,0.00009529817,0.00008160969,0.0003780571,0.000004203351,0.000757934,0.8501066,0.1257074,0.0008571759,0.0006241912,0.02124035],"study_design_scores_gemma":[0.0003669261,0.00009769054,0.000307633,0.0001066658,0.0002385537,0.00004910488,0.0001092377,0.9732753,0.01465278,0.00001721894,0.01053442,0.0002444473],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04239837,0.0001128154,0.9555965,0.0001311078,0.001169941,0.0003029699,0.00001208991,0.0002186114,0.00005757121],"genre_scores_gemma":[0.9051057,0.00003688385,0.09379346,0.0001332843,0.0004568948,0.00002129757,0.00002220001,0.00007352843,0.0003567492],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8627073,"threshold_uncertainty_score":0.9999962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0241363560064933,"score_gpt":0.274060954240077,"score_spread":0.2499245982335837,"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."}}