{"id":"W2332472109","doi":"10.1109/idam.2014.6912679","title":"Neural network-based decision support for conceptual design of a mechatronic system using mechatronic multi-criteria profile (MMP)","year":2014,"lang":"en","type":"article","venue":"","topic":"Sensor Technology and Measurement Systems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Mechatronics; Flexibility (engineering); Artificial neural network; Conceptual design; Computer science; Artificial intelligence; Control engineering; Reliability (semiconductor); Systems engineering; Engineering; Machine learning; Human–computer interaction","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001780579,0.0009729558,0.0007300698,0.0007268324,0.0004403642,0.001279716,0.000869138,0.00142239,0.002141843],"category_scores_gemma":[0.00372121,0.0004197805,0.000532731,0.0005159444,0.0005009374,0.0008887533,0.0009603419,0.001044405,0.0002252022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001101375,"about_ca_system_score_gemma":0.0009236016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005754193,"about_ca_topic_score_gemma":0.004902964,"domain_scores_codex":[0.9991388,0.0003507395,0.00006647313,0.0001414942,0.0002151869,0.00008716578],"domain_scores_gemma":[0.9985685,0.0008941911,0.0001384896,0.00003075066,0.0003223065,0.00004570654],"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":[0.0001187147,0.00007659234,0.0005559608,0.00007948864,0.00004787498,0.00007791469,0.00006416415,0.951664,0.001768495,0.002550309,0.0003070526,0.04268943],"study_design_scores_gemma":[0.000004344673,0.00001912933,0.00004547604,0.00000416945,0.000004591293,0.000003121062,0.000003920371,0.9991273,0.0002144651,0.0005193821,0.00005198477,0.000002063116],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03942712,0.0002084916,0.9566196,0.0002119418,0.0000336902,0.00008997001,0.00003227967,0.0003288717,0.003047941],"genre_scores_gemma":[0.9199505,0.000126585,0.0782038,0.000112197,0.00002358886,0.0002410446,0.00007464834,0.00002558852,0.00124207],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005754193,"threshold_uncertainty_score":0.01144141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07620990505478702,"score_gpt":0.2891202913420159,"score_spread":0.2129103862872289,"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."}}