{"id":"W4410767107","doi":"10.4271/02-18-04-0023","title":"Design Space Exploration of a Continuous Rubber Track System via Surrogate Modeling","year":2025,"lang":"en","type":"article","venue":"SAE International journal of commercial vehicles","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Track (disk drive); Natural rubber; Space (punctuation); Computer science; Aerospace engineering; Engineering; Mechanical engineering; Materials science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006370361,0.0001481474,0.0003218044,0.000438902,0.00007418347,0.0001120213,0.0009838149,0.00006840286,0.00000382195],"category_scores_gemma":[0.0001459631,0.0001421697,0.0001344128,0.0003251022,0.00004864119,0.001589393,0.0001418563,0.0002048783,0.000004648066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002081319,"about_ca_system_score_gemma":0.0001870778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002601451,"about_ca_topic_score_gemma":0.000009101623,"domain_scores_codex":[0.9981115,0.0002166025,0.0007709319,0.0001752596,0.0005777688,0.0001479711],"domain_scores_gemma":[0.9966598,0.0002518198,0.0006478972,0.0001814817,0.002199587,0.00005938086],"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":[0.0002877605,0.0002412123,0.0003219411,0.00002463851,0.0002753963,0.00005908326,0.001486212,0.8532189,0.007964391,0.02436599,0.0001693564,0.1115852],"study_design_scores_gemma":[0.001537697,0.0001048041,0.0005594157,0.0003555764,0.00002608938,0.00006012481,0.0003463728,0.9775293,0.01298177,0.006170716,0.0001832468,0.0001448676],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01073808,0.0001854263,0.9853857,0.001736853,0.001419501,0.0001548439,0.000003409626,0.00004196308,0.0003342273],"genre_scores_gemma":[0.7833273,0.00004580415,0.2163399,0.0001058565,0.000121841,0.000004087688,0.000001410202,0.000008976478,0.000044778],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7725893,"threshold_uncertainty_score":0.5797511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03108365034165497,"score_gpt":0.2975784642349674,"score_spread":0.2664948138933124,"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."}}