{"id":"W2795851179","doi":"10.4271/2018-01-1339","title":"Parameter Identification and Validation for Combined Slip Tire Models Using a Vehicle Measurement System","year":2018,"lang":"en","type":"article","venue":"SAE International journal of vehicle dynamics, stability, and NVH","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Centres of Excellence","keywords":"Slip (aerodynamics); Identification (biology); Computer science; Automotive engineering; Environmental science; Engineering; Aerospace engineering; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001206432,0.000155184,0.0002688835,0.000142445,0.0001011931,0.0002011878,0.0002018817,0.00008736663,0.000003051025],"category_scores_gemma":[0.00007219899,0.0001530224,0.00009322527,0.00006316524,0.00008596219,0.0004281576,0.00004179937,0.0001156916,6.744615e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000550373,"about_ca_system_score_gemma":0.00003809754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005845134,"about_ca_topic_score_gemma":0.0001391184,"domain_scores_codex":[0.9983687,0.0000596477,0.0007206564,0.0001911029,0.0004828138,0.0001770973],"domain_scores_gemma":[0.9980898,0.00008614277,0.0002647543,0.0001463594,0.001314833,0.00009809106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003381412,0.001253714,0.146668,0.003898528,0.004646223,0.00004006156,0.007115705,0.04851315,0.5218136,0.05309575,0.0002182922,0.2093555],"study_design_scores_gemma":[0.001294596,0.0001497451,0.00772001,0.0001604847,0.00005669729,0.00003559493,0.0003556414,0.9873542,0.0007072339,0.00201247,0.00001350082,0.000139877],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9317645,0.0002361931,0.06624326,0.0001685933,0.001125422,0.0002887221,0.00007842987,0.00003664247,0.00005823594],"genre_scores_gemma":[0.9991873,0.00004071038,0.0004141258,0.00001303666,0.0002898831,0.00001022945,0.00001172134,0.0000271068,0.000005907122],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.938841,"threshold_uncertainty_score":0.6240071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03234781519232578,"score_gpt":0.2477314536927344,"score_spread":0.2153836385004086,"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."}}