{"id":"W2058856769","doi":"10.1016/j.commatsci.2014.01.012","title":"A micromechanical model of particle-reinforced metal matrix composites considering particle size and damage","year":2014,"lang":"en","type":"article","venue":"Computational Materials Science","topic":"Composite Material Mechanics","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Composite material; Weibull distribution; Volume fraction; Homogenization (climate); Composite number; Particle (ecology); Metal matrix composite; Dislocation; Nonlinear system; Micromechanics; Mathematics","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":[0.000195038,0.0004657895,0.0006201391,0.0004263459,0.0006153373,0.000687451,0.001445264,0.002679166,0.002929483],"category_scores_gemma":[0.0004579875,0.000474785,0.0006116389,0.0003589895,0.0007440648,0.0007329649,0.0004969235,0.0006784057,0.0005355796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005283598,"about_ca_system_score_gemma":0.0008391708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008786639,"about_ca_topic_score_gemma":0.007490156,"domain_scores_codex":[0.9998947,0.00001867517,0.000005075903,0.00002703873,0.00003947615,0.00001500707],"domain_scores_gemma":[0.9998522,0.00004941858,0.00002661058,0.00001628532,0.00003558886,0.00001983289],"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":[0.00001420799,0.00003098167,0.0002010957,0.0000367728,0.000009998283,0.0001727075,0.0000361324,0.9769344,0.006923135,0.01342055,0.0003307235,0.001889324],"study_design_scores_gemma":[0.000002948966,0.000006947331,0.0001106623,0.000001994377,0.000002441652,0.00001722457,0.000006211622,0.9983521,0.0002498877,0.000934482,0.0003111763,0.000003983297],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2437953,0.001155856,0.6638419,0.001591253,0.0004653794,0.0001580259,0.0005315652,0.0006129859,0.08784768],"genre_scores_gemma":[0.944463,0.0004638442,0.02816238,0.0001496199,0.00007906982,0.0001339074,0.0001235013,0.0001218823,0.02630273],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008786639,"threshold_uncertainty_score":0.01747102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01350879107192534,"score_gpt":0.2335003240632587,"score_spread":0.2199915329913334,"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."}}