{"id":"W2042599535","doi":"10.1007/s10704-012-9779-y","title":"Multiscale Model to Study of Fracture Toughening in Graphene/Polymer Nanocomposite","year":2012,"lang":"en","type":"article","venue":"International Journal of Fracture","topic":"Carbon Nanotubes in Composites","field":"Materials Science","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Materials science; Graphene; Composite material; Polymer nanocomposite; Nanocomposite; Toughening; Polymer; Finite element method; Multiscale modeling; Fracture (geology); Cohesive zone model; Structural engineering; Nanotechnology; Toughness; Engineering","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":[0.0002114049,0.0005544673,0.0007827362,0.0006103398,0.0005192267,0.0005945117,0.001412933,0.001967986,0.00256422],"category_scores_gemma":[0.0005567268,0.0003584503,0.0009726514,0.0003686485,0.000802108,0.0007134342,0.0006631488,0.0008192472,0.0001762613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007205132,"about_ca_system_score_gemma":0.0006428279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00709866,"about_ca_topic_score_gemma":0.005093445,"domain_scores_codex":[0.9998751,0.00002939366,0.00000475536,0.00002753789,0.00003561725,0.00002753598],"domain_scores_gemma":[0.9997831,0.00008226829,0.00003578085,0.00001996913,0.0000410848,0.00003785271],"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":[0.00006435464,0.0001857927,0.0008640898,0.0001209262,0.00006841317,0.0004048842,0.00007202967,0.9133435,0.02535698,0.05665834,0.0005765448,0.002284128],"study_design_scores_gemma":[0.000004910648,0.000007543557,0.0001751836,0.000002223377,0.000004561135,0.00001450007,0.000006913365,0.9977046,0.0002556887,0.00169635,0.0001229349,0.000004643241],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5975875,0.001720591,0.3532328,0.001514462,0.0003509978,0.0001644688,0.0005676882,0.0003276808,0.04453379],"genre_scores_gemma":[0.978822,0.0002943482,0.01320867,0.0001027502,0.00007190949,0.00009526705,0.00009059842,0.00005784794,0.007256689],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00709866,"threshold_uncertainty_score":0.01411474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01475048725724185,"score_gpt":0.3062068563607978,"score_spread":0.2914563691035559,"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."}}