{"id":"W2735445600","doi":"10.1177/0954407017713103","title":"Design and optimization of a cam-actuated electrohydraulic brake system","year":2017,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering","topic":"Hydraulic and Pneumatic Systems","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Brake; Automotive engineering; Automotive industry; Hydraulic brake; Mechanism (biology); Brake pad; Engineering; Torque; Component (thermodynamics); Disc brake; Mechanical engineering; Control engineering; Computer 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003054159,0.0005236189,0.0007160454,0.0003062428,0.0003465206,0.0006845861,0.000663524,0.0006830713,0.001900518],"category_scores_gemma":[0.0003372131,0.0003871595,0.0003004963,0.0002163571,0.000335128,0.0003427535,0.0004203089,0.000321322,0.0003990691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003844293,"about_ca_system_score_gemma":0.0008696442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00164566,"about_ca_topic_score_gemma":0.001924758,"domain_scores_codex":[0.999751,0.00004491822,0.00001356254,0.00005328517,0.0001037916,0.00003334393],"domain_scores_gemma":[0.9998407,0.00003931559,0.00004081392,0.00001101991,0.00005787351,0.00001021197],"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":[0.0001970203,0.00005812306,0.0005771265,0.0004033951,0.00005844534,0.0002152382,0.00006998941,0.8666724,0.09037647,0.004830559,0.0006403773,0.03590091],"study_design_scores_gemma":[0.00004336269,0.0001863864,0.0004386829,0.00001305473,0.00002181815,0.00003577243,0.00001517972,0.990294,0.00632902,0.0002883172,0.002322786,0.00001166552],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1341321,0.001022841,0.8408134,0.0002286201,0.0001151612,0.0002951263,0.0001461355,0.0005164378,0.0227302],"genre_scores_gemma":[0.9537695,0.0002526347,0.04159905,0.00002829729,0.00001177105,0.0002500031,0.00005933146,0.00001979129,0.00400957],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001900518,"threshold_uncertainty_score":0.006357908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00986642356561691,"score_gpt":0.1964896579382712,"score_spread":0.1866232343726543,"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."}}