{"id":"W2761733866","doi":"10.1016/b978-0-12-811718-7.00011-3","title":"Smoothed Particle Hydrodynamics Method and Its Applications to Cardiovascular Flow Modeling","year":2017,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Fluid Dynamics Simulations and Interactions","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Smoothed-particle hydrodynamics; Discretization; Inviscid flow; Material point method; Benchmark (surveying); Computer science; Flow (mathematics); Mechanics; Applied mathematics; Physics; Mathematics; Finite element method; Geology; Mathematical analysis","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":[0.0001722609,0.00029955,0.0004077125,0.0001126231,0.0002409374,0.0001039644,0.0001986968,0.0001937398,0.00002567963],"category_scores_gemma":[0.0000136392,0.0003321393,0.0002584039,0.000009103812,0.00001638998,0.0000775458,0.00008290521,0.0003011793,0.0001156087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000100904,"about_ca_system_score_gemma":0.00002044333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001075933,"about_ca_topic_score_gemma":0.00002815961,"domain_scores_codex":[0.9989507,0.00001043345,0.0003093641,0.0003449611,0.0001674035,0.000217093],"domain_scores_gemma":[0.9988109,0.00004171907,0.00003579899,0.0008553071,0.0001030927,0.0001531209],"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":[8.847065e-7,0.000001348666,9.304903e-8,0.00003232118,0.0001999637,0.000001150053,0.00005729882,0.5557767,0.00005620804,0.003965835,0.000003092107,0.4399052],"study_design_scores_gemma":[0.00006948685,0.00000540965,3.745924e-7,0.00006216214,0.0001387731,0.000006066548,0.000001343879,0.6449608,0.000006923943,0.002249354,0.3522713,0.0002280536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00009585116,0.002142585,0.2368882,0.00001966407,0.0001941044,0.0007258657,0.00009636642,0.0001881765,0.7596492],"genre_scores_gemma":[0.04998405,0.0006081456,0.02217075,0.00005612345,0.0004069708,0.0004363926,0.00006339854,0.0003109336,0.9259632],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4396771,"threshold_uncertainty_score":0.999913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01946227946018807,"score_gpt":0.2577355361451344,"score_spread":0.2382732566849463,"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."}}