{"id":"W2047815456","doi":"10.4271/2013-01-1722","title":"Valve Lift Profile Development and Optimization Using Matlab","year":2013,"lang":"en","type":"article","venue":"SAE International Journal of Engines","topic":"Hydraulic and Pneumatic Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"MATLAB; Lift (data mining); Computer science; Automotive engineering; Aerospace engineering; Marine engineering; Simulation; Engineering; Data mining","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":[0.0001014106,0.00007710757,0.0001091585,0.0001269701,0.00001587698,0.00006328744,0.0001087463,0.00003264984,0.000172325],"category_scores_gemma":[0.00003141209,0.00006436118,0.00003372684,0.00004152193,0.000008211428,0.0002462396,0.00001401664,0.00006064839,0.00001605769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005104186,"about_ca_system_score_gemma":0.00002315368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008180456,"about_ca_topic_score_gemma":8.213003e-7,"domain_scores_codex":[0.9993517,0.000008599559,0.0003234956,0.00003975782,0.0002009597,0.00007549262],"domain_scores_gemma":[0.9995774,0.00003156011,0.00008164074,0.00003356041,0.0002259381,0.00004991753],"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":[0.000002308561,0.00001358188,0.001610107,0.00004532123,0.0002800933,0.000007540498,0.000868007,0.9831125,0.001970135,0.00006285359,0.001109924,0.01091761],"study_design_scores_gemma":[0.0005178882,0.00002037301,0.009376355,0.0004012267,0.00002049966,0.000478651,0.0002900093,0.9804207,0.001919178,0.00009176767,0.006262074,0.0002012518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8028345,0.0006424196,0.1934009,0.0001001435,0.001742626,0.0001012489,0.000001957746,0.00003785764,0.001138379],"genre_scores_gemma":[0.9400751,0.00004630399,0.05946046,0.00001995559,0.000317253,0.000003334218,0.000003076305,0.00001438589,0.00006014328],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1372406,"threshold_uncertainty_score":0.2624573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01194667293464895,"score_gpt":0.2242243071188456,"score_spread":0.2122776341841967,"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."}}