{"id":"W3174825660","doi":"10.1016/j.jsv.2021.116320","title":"Hybrid uncertainties-based analysis and optimization methods for axial friction force of drive-shaft systems","year":2021,"lang":"en","type":"article","venue":"Journal of Sound and Vibration","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Natural Science Foundation of Guangdong Province; National Natural Science Foundation of China","keywords":"Control theory (sociology); Torque; Engineering; Vibration; Drive shaft; Structural engineering; Computer science; Mechanical engineering; Physics","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":[0.002000054,0.00006775636,0.0002988903,0.0003237517,0.00009161946,0.0001734447,0.00006324719,0.00004481126,0.00001309218],"category_scores_gemma":[0.001587247,0.00004899227,0.0001080767,0.000446362,0.00003231511,0.0002962873,0.00001060352,0.00004975559,6.864311e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002129999,"about_ca_system_score_gemma":0.00007207457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003836246,"about_ca_topic_score_gemma":0.000001141475,"domain_scores_codex":[0.998783,0.0001658739,0.0005850139,0.0001286961,0.0002707294,0.00006671296],"domain_scores_gemma":[0.9975808,0.001019674,0.0004847045,0.00009533293,0.0007684535,0.00005108269],"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":[0.00005345255,0.00001837715,0.0005722653,0.00002790589,0.00009573629,7.190268e-7,0.0001017674,0.9914021,0.003220884,0.001105271,0.00004900378,0.003352513],"study_design_scores_gemma":[0.0003701212,0.000139378,0.0006068665,0.00002017833,0.0002569873,0.00001559644,0.0002413146,0.9898868,0.002398343,0.005893048,0.0001157154,0.00005563939],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02442598,0.0004749359,0.9746203,0.00009561951,0.0002775823,0.00007617536,0.000006940842,0.00000389941,0.00001857182],"genre_scores_gemma":[0.7290767,0.00004343254,0.2707186,0.00001320016,0.00009145295,0.000001442299,0.000007166901,0.000003706956,0.00004431195],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7046507,"threshold_uncertainty_score":0.1997847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05596357921353103,"score_gpt":0.3613063900426888,"score_spread":0.3053428108291578,"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."}}