{"id":"W4396865448","doi":"10.3390/polym16101374","title":"Investigation of Macroscopic Mechanical Behavior of Magnetorheological Elastomers under Shear Deformation Using Microscale Representative Volume Element Approach","year":2024,"lang":"en","type":"article","venue":"Polymers","topic":"Vibration Control and Rheological Fluids","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Representative elementary volume; Magnetorheological fluid; Composite material; Hyperelastic material; Carbonyl iron; Microscale chemistry; Micromechanics; Viscoelasticity; Silicone rubber; Elastomer; Volume fraction; Deformation (meteorology); Isotropy; Finite element method; Magnetic field; Composite number; Microstructure; Structural engineering","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":[0.0001446138,0.0001248569,0.0002065092,0.0001073059,0.00003252407,0.00001760407,0.00008418047,0.000119771,0.0002917589],"category_scores_gemma":[0.0000111732,0.0001036147,0.00008797232,0.0002537156,0.0001544942,0.0001756799,0.00003338877,0.0001229868,0.000007740307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006446662,"about_ca_system_score_gemma":0.0000251561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004576917,"about_ca_topic_score_gemma":0.000001093805,"domain_scores_codex":[0.9989921,0.00005915208,0.0004120363,0.0001681955,0.000187693,0.00018078],"domain_scores_gemma":[0.9997168,0.00003849766,0.00003891816,0.0001086626,0.00002854586,0.00006853165],"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":[0.00001818736,0.0000237288,0.001970403,0.0001607945,0.0000602522,0.000001405966,0.0004130604,0.01307187,0.9783906,0.00459643,0.000104578,0.00118866],"study_design_scores_gemma":[0.0003943468,0.0001731413,0.005471937,0.00004676269,0.0001162009,0.00001030691,0.0005543227,0.6989025,0.2937979,0.0003005599,0.00003777439,0.0001941961],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7905265,0.0006906041,0.2077433,0.00005075842,0.000289373,0.0002279677,0.00002653692,0.0001094709,0.0003354871],"genre_scores_gemma":[0.993936,0.00002351359,0.005791724,0.00002589934,0.00003287231,0.00002755922,0.00003770032,0.00001399541,0.0001107473],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6858307,"threshold_uncertainty_score":0.4225285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02396337117784368,"score_gpt":0.2554707558315453,"score_spread":0.2315073846537016,"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."}}