{"id":"W2109253735","doi":"10.1115/imece2013-64978","title":"Multiscale Modeling of Nano-Reinforced Structural Adhesive Bonds","year":2013,"lang":"en","type":"article","venue":"","topic":"Carbon Nanotubes in Composites","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Adhesive; Carbon nanotube; Representative elementary volume; Composite material; Nano-; Constitutive equation; Finite element method; Nanoscopic scale; Continuum mechanics; Multiscale modeling; Micromechanics; Nonlinear system; Nanometre; Nanotechnology; Mechanics; Computational chemistry; Thermodynamics; Composite number; Microstructure; Layer (electronics); Chemistry; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001765624,0.0002656251,0.0003472994,0.0002699618,0.0002204295,0.0004534707,0.0006324861,0.0008442787,0.0008063728],"category_scores_gemma":[0.0005091395,0.0002071635,0.000379467,0.0001916474,0.0004783679,0.0006294766,0.0004219401,0.0003471191,0.000116139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004100765,"about_ca_system_score_gemma":0.0003965642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001423786,"about_ca_topic_score_gemma":0.001218066,"domain_scores_codex":[0.9998903,0.00002309129,0.000004572235,0.00002124992,0.00004544801,0.0000154064],"domain_scores_gemma":[0.9998555,0.00005452583,0.00003371972,0.00001880885,0.00002157321,0.00001582684],"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":[0.0000119967,0.00004382155,0.0004354758,0.00003247226,0.0000160395,0.0001174883,0.00006328372,0.9277273,0.04341302,0.024855,0.000094221,0.003189846],"study_design_scores_gemma":[0.000001216926,0.000006486215,0.00011811,0.000001173364,0.000001474855,0.00000997283,0.000005034372,0.9974949,0.0007818334,0.001433587,0.0001438608,0.0000023905],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4688867,0.0004289578,0.5200313,0.0002702862,0.00004642532,0.00004234885,0.0001019661,0.0001987424,0.009993291],"genre_scores_gemma":[0.9759813,0.000226838,0.02189089,0.00002862366,0.00001137228,0.0000546931,0.00003442135,0.00002569548,0.001746134],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001423786,"threshold_uncertainty_score":0.002975345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01103522747567112,"score_gpt":0.2372831680227717,"score_spread":0.2262479405471006,"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."}}