{"id":"W2404652880","doi":"10.2316/journal.206.2015.5.206-4325","title":"INTELLIGENT FAULT-TOLERANT CONTROL OF LINEAR DRIVES USING SOFT COMPUTING","year":2015,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Data Processing Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science; Soft computing; Fault tolerance; Control (management); Fault (geology); Embedded system; Distributed computing; Artificial intelligence; Artificial neural network; Geology; Seismology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002665668,0.0003482933,0.0004389539,0.000262712,0.0004175832,0.0008955606,0.0004134593,0.0002978148,0.00078984],"category_scores_gemma":[0.0008954104,0.0001741565,0.0002451822,0.0002389125,0.0004671325,0.0004829213,0.0006075424,0.0004134857,0.0001158124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003489065,"about_ca_system_score_gemma":0.0004519293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001569537,"about_ca_topic_score_gemma":0.001748785,"domain_scores_codex":[0.9998074,0.00003544913,0.00001585978,0.00003853056,0.00007051273,0.00003226659],"domain_scores_gemma":[0.9995362,0.0002030122,0.00008677529,0.00003685358,0.0001147827,0.00002246305],"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":[0.0002915921,0.00009637127,0.0007681398,0.0001751743,0.00005376703,0.0001348458,0.0001953605,0.7947421,0.02896133,0.01064262,0.0006997403,0.1632389],"study_design_scores_gemma":[0.0000066828,0.00007065815,0.0001577113,0.000005879081,0.000005941062,0.00001408414,0.00001115608,0.9943486,0.003008237,0.002123927,0.0002432914,0.000003809244],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1343655,0.000474307,0.8586417,0.0002845314,0.0001178262,0.000046926,0.00001847411,0.0004456169,0.005605078],"genre_scores_gemma":[0.9859495,0.00006878829,0.01305143,0.00002903436,0.00001025653,0.00002156916,0.000007857273,0.000007412157,0.0008541884],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001569537,"threshold_uncertainty_score":0.00312072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02623902885826527,"score_gpt":0.3042923579365525,"score_spread":0.2780533290782872,"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."}}