{"id":"W1963855776","doi":"10.1115/1.1336797","title":"Adapting an Articulated Vehicle to its Drivers","year":2000,"lang":"en","type":"article","venue":"Journal of Mechanical Design","topic":"Soil Mechanics and Vehicle Dynamics","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Yaw; Axle; Tractor; Suspension (topology); Automotive engineering; Articulated vehicle; Vehicle dynamics; Engineering; Control theory (sociology); Simulation; Chassis; Reduction (mathematics); Automobile handling; Rollover (web design); Computer science; Control (management); Truck; Artificial intelligence; Mathematics","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":[0.0006028969,0.0001341092,0.0002322004,0.00008771713,0.00004717942,0.00004593763,0.0002448802,0.0001097128,0.0002572902],"category_scores_gemma":[0.00006082599,0.0001244814,0.00009114929,0.0002380003,0.000003589895,0.0002243238,0.00001205944,0.0002830067,0.0001026102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008085868,"about_ca_system_score_gemma":0.00002311142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001403871,"about_ca_topic_score_gemma":0.000001227514,"domain_scores_codex":[0.9988234,0.00007658937,0.0004206959,0.0001095792,0.0002896826,0.00028002],"domain_scores_gemma":[0.9992767,0.00005891133,0.00005231776,0.0001426053,0.0001073553,0.0003620902],"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":[0.0001252819,0.00009964841,0.000005196147,0.00001214505,0.00009220722,0.0001706655,0.0002236613,0.5741135,0.2051874,0.001467178,0.0004463807,0.2180567],"study_design_scores_gemma":[0.0004453354,0.0004562203,0.00007866399,0.00004929942,0.00003051456,0.00006561013,0.00004510272,0.9812444,0.01624007,0.0006913281,0.0004891865,0.0001642346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9013014,0.00005191242,0.0979126,0.0001097629,0.0002921846,0.0001098963,0.000001598346,0.00009012918,0.000130508],"genre_scores_gemma":[0.9893995,0.00006020695,0.01017714,0.0001464188,0.0001418949,0.000001624959,3.858632e-7,0.00003713106,0.00003571527],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4071309,"threshold_uncertainty_score":0.5076204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02403636483701325,"score_gpt":0.2297428880271277,"score_spread":0.2057065231901144,"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."}}