{"id":"W2528978386","doi":"10.1002/cnm.2836","title":"Non‐Newtonian versus numerical rheology: Practical impact of shear‐thinning on the prediction of stable and unstable flows in intracranial aneurysms","year":2016,"lang":"en","type":"article","venue":"International Journal for Numerical Methods in Biomedical Engineering","topic":"Intracranial Aneurysms: Treatment and Complications","field":"Medicine","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Rheology; Computational fluid dynamics; Shear thinning; Mechanics; Newtonian fluid; Non-Newtonian fluid; Generalized Newtonian fluid; Aneurysm; Shear stress; Computer science; Materials science; Shear rate; Mathematics; Physics; Thermodynamics; Surgery; Medicine","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":[0.002039549,0.0005390319,0.0004160496,0.0005795336,0.0002620501,0.001185079,0.0003599967,0.0005458403,0.0005359527],"category_scores_gemma":[0.009022471,0.0002215906,0.0003849154,0.0002666439,0.0005602303,0.0009628274,0.0007184388,0.0004498951,0.0001465344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001838705,"about_ca_system_score_gemma":0.0005851181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001752244,"about_ca_topic_score_gemma":0.001350625,"domain_scores_codex":[0.9994697,0.0002364273,0.00004993448,0.00008620256,0.0001248995,0.00003287202],"domain_scores_gemma":[0.9970477,0.001959013,0.0003877687,0.0002946507,0.0002264525,0.00008446417],"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":[0.0008661998,0.0002304659,0.0743648,0.0003403812,0.0001497951,0.0005250231,0.0004242827,0.6985991,0.07878448,0.005376437,0.000393018,0.139946],"study_design_scores_gemma":[0.0000188495,0.0001721093,0.01007276,0.00003594114,0.00003499088,0.0001248112,0.00005933559,0.967361,0.02031109,0.001383718,0.0003954406,0.00002997321],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9098772,0.001540932,0.08574228,0.0004979628,0.0000500456,0.00003623019,0.0000553753,0.0001682003,0.002031873],"genre_scores_gemma":[0.9829311,0.0003908239,0.01636276,0.00002447366,0.00001839753,0.000008861771,0.00003398344,0.0000378791,0.0001917593],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002039549,"threshold_uncertainty_score":0.01078629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03812745030352499,"score_gpt":0.3876293254937623,"score_spread":0.3495018751902373,"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."}}