{"id":"W4307052046","doi":"10.1007/s40964-022-00352-0","title":"Evolutionary computation to design additively manufactured optimal heterogeneous lattice structures","year":2022,"lang":"en","type":"article","venue":"Progress in Additive Manufacturing","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"Harrison McCain Foundation; Mitacs","keywords":"Computation; Lattice (music); Genetic algorithm; Mathematical optimization; Computer science; Observable; Optimization algorithm; Global optimization; Algorithm; Evolutionary algorithm; Mathematics; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002871645,0.0005573984,0.0004468414,0.0007647465,0.0005089663,0.00009976028,0.0006567349,0.0001321569,0.0006849229],"category_scores_gemma":[0.00006118073,0.0006273089,0.0001237058,0.0003076565,0.000158346,0.0002067374,0.0007354784,0.0009833155,0.00005192557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007205939,"about_ca_system_score_gemma":0.00003214215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009408028,"about_ca_topic_score_gemma":0.000003454799,"domain_scores_codex":[0.9970472,0.0002440201,0.0004984877,0.0007422703,0.0005752588,0.0008927],"domain_scores_gemma":[0.9989452,0.0003945669,0.0001232909,0.0003443919,0.00004558447,0.0001469294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001338483,0.00006643524,0.00009666765,0.00005076802,0.0001173652,0.000272461,0.0006560946,0.7508152,0.0000395502,0.0001185548,0.003772216,0.2438609],"study_design_scores_gemma":[0.001574703,0.0006446856,0.06155832,0.0001436715,0.00006311882,0.0003282397,0.001513806,0.05101694,0.8421151,0.009369048,0.02936225,0.002310098],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9047247,0.0009446989,0.08557893,0.0002649901,0.001163819,0.001896263,0.001123036,0.00349197,0.0008115929],"genre_scores_gemma":[0.9579882,0.00001757291,0.04037468,0.0001054505,0.0001235864,0.001010783,0.0002254005,0.0001165505,0.00003777979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8420756,"threshold_uncertainty_score":0.9996178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01969532098739531,"score_gpt":0.2477308288638362,"score_spread":0.2280355078764409,"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."}}