{"id":"W2967617290","doi":"10.1016/j.compositesb.2019.107311","title":"Experimental characterization and microscale modeling of isotropic and anisotropic magnetorheological elastomers","year":2019,"lang":"en","type":"article","venue":"Composites Part B Engineering","topic":"Vibration Control and Rheological Fluids","field":"Engineering","cited_by":88,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Magnetorheological fluid; Microscale chemistry; Materials science; Isotropy; Anisotropy; Carbonyl iron; Elastomer; Composite material; Silicone rubber; Rheometer; Magnetorheological elastomer; Characterization (materials science); Magnetic field; Rheology; Nanotechnology; Optics; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002533539,0.0001303143,0.000200501,0.00005464668,0.0000236757,0.00002170933,0.00004850492,0.0000707446,0.0000511368],"category_scores_gemma":[0.000003881703,0.0001208731,0.0000246267,0.0000593895,0.00002309406,0.0001236652,0.00004230697,0.0000791773,0.000006209072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001270224,"about_ca_system_score_gemma":0.000001777111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.489168e-7,"about_ca_topic_score_gemma":5.701463e-8,"domain_scores_codex":[0.9994569,0.000007826741,0.000184046,0.0001415964,0.00005960012,0.0001500232],"domain_scores_gemma":[0.9998101,0.00002487218,0.00001309569,0.00007941587,0.00001282126,0.00005969907],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006352071,0.00000850465,0.003911246,0.00005058219,0.00001256936,6.14401e-7,0.00004360691,0.09060219,0.904424,0.0007917382,0.000002336126,0.0001462252],"study_design_scores_gemma":[0.0003504497,0.0001017478,0.006665313,0.00002651786,0.000006787776,0.000007550942,0.00001005565,0.9510397,0.04141755,0.000003095961,0.0002370944,0.0001340763],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9294878,0.001154779,0.06880577,0.00001249261,0.0001986046,0.00011375,0.000004777286,0.0001307261,0.00009131076],"genre_scores_gemma":[0.9984915,0.00009942344,0.001271077,0.0000136369,0.00004284184,0.000007950838,0.00001667366,0.0000145449,0.00004238729],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8630065,"threshold_uncertainty_score":0.492906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005013713509610074,"score_gpt":0.1737189330349234,"score_spread":0.1687052195253133,"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."}}