{"id":"W2621079678","doi":"10.1515/tjj-2017-0010","title":"Optimization Design and Experimental Study of a Two-disk Rotor System Based on Multi-Island Genetic Algorithm","year":2017,"lang":"en","type":"article","venue":"International Journal of Turbo and Jet Engines","topic":"Magnetic Bearings and Levitation Dynamics","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Critical speed; Rotor (electric); Helicopter rotor; Amplitude; Vibration; Genetic algorithm; Position (finance); Control theory (sociology); Computer science; Optimal design; Range (aeronautics); Engineering; Algorithm; Acoustics; Physics; Mechanical engineering; Aerospace engineering; Optics; Artificial intelligence","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":[0.0001130353,0.00008919583,0.0001337624,0.0001175947,0.00003814436,0.00009227375,0.0001295206,0.00002394515,0.0000113451],"category_scores_gemma":[0.00002407505,0.00007358046,0.00002395834,0.00001292397,0.0000187285,0.00009687225,0.00001638307,0.00006060379,1.556368e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000213446,"about_ca_system_score_gemma":0.000007461078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001642586,"about_ca_topic_score_gemma":0.00000236078,"domain_scores_codex":[0.9994447,0.00001913169,0.0002333968,0.00006481144,0.0001858256,0.00005218486],"domain_scores_gemma":[0.999574,0.00004587614,0.0001452329,0.00007180839,0.0001212726,0.00004181429],"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":[0.0000342392,0.0001153265,0.002068925,0.00001934204,0.00006819971,0.00002191738,0.000354374,0.992611,0.0002765972,0.00001187954,0.00001146637,0.00440672],"study_design_scores_gemma":[0.002254997,0.0003273521,0.007807517,0.00009011797,0.00001992778,0.00003450502,0.0002092884,0.9887072,0.0004677118,0.000003004364,0.000009372281,0.00006903882],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5904602,0.0002354416,0.4085067,0.00002340118,0.0005300039,0.0001680848,0.000008203869,0.00001195702,0.00005599057],"genre_scores_gemma":[0.9280417,0.00002267367,0.07180458,0.000004667853,0.0001002235,0.000005120485,9.271246e-7,0.0000102944,0.000009801598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3375815,"threshold_uncertainty_score":0.3000524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01344950415755894,"score_gpt":0.2589834333930931,"score_spread":0.2455339292355342,"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."}}