{"id":"W2258577786","doi":"10.4271/2002-01-1395","title":"Utilization of Statistical Techniques in a Two Step Parameter Estimation for a Hydraulic Valve","year":2002,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Hydraulic and Pneumatic Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Hydraulic machinery; Estimation theory; Estimation; Engineering; Mechanical engineering; Algorithm; Systems engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000691575,0.0006136376,0.001067429,0.0003368783,0.0001033442,0.00005958185,0.000538437,0.0005500183,0.0003520887],"category_scores_gemma":[0.00117177,0.0005635229,0.0003503679,0.0007237438,0.000429849,0.0003621262,0.00009225866,0.0005989344,0.00005278808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002826647,"about_ca_system_score_gemma":0.00002690677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006555796,"about_ca_topic_score_gemma":0.0130061,"domain_scores_codex":[0.996228,0.000150878,0.001564886,0.0006813155,0.0006469696,0.0007279416],"domain_scores_gemma":[0.997287,0.001318359,0.0001968599,0.0008871328,0.00008853352,0.0002221025],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002066197,0.0007325668,0.000333375,0.000939712,0.0001332639,0.00002550184,0.0002571562,0.002329674,0.8307104,0.02588262,0.01196308,0.126486],"study_design_scores_gemma":[0.003200043,0.002852406,0.9152933,0.001994594,0.00028921,0.000187943,0.0002131431,0.002082809,0.001624918,0.01656808,0.05345912,0.002234394],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6492419,0.004979766,0.03294089,0.004980239,0.002039707,0.02510494,0.001383258,0.02548244,0.2538469],"genre_scores_gemma":[0.9554868,0.0002083977,0.04252067,0.0003873669,0.00007124871,0.001045224,0.0000791484,0.0001333092,0.00006787497],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.91496,"threshold_uncertainty_score":0.9996817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02472635088104196,"score_gpt":0.2817572714773369,"score_spread":0.257030920596295,"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."}}