{"id":"W6923242741","doi":"10.1371/journal.pone.0179485.g007","title":"Comparison among incremental damping details based on (a) front quarter vehicle model sprung mass response, (b) the corresponding unsprung mass response, (c) rear quarter vehicle model sprung mass response and (d) the corresponding unsprung mass response.","year":2017,"lang":"en","type":"other","venue":"Figshare","topic":"Educational Robotics and Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sprung mass; Front (military); Quarter (Canadian coin); Control theory (sociology); Toe","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","research_integrity"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.008897508,0.001881051,0.001763177,0.001801246,0.002322048,0.002454104,0.004342049,0.0009408335,0.0008857884],"category_scores_gemma":[0.005798963,0.00155523,0.0006202499,0.001043286,0.0003385526,0.001124652,0.000835908,0.002494546,0.0004417037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001352824,"about_ca_system_score_gemma":0.00152975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001299594,"about_ca_topic_score_gemma":0.0001283719,"domain_scores_codex":[0.9863864,0.00486932,0.001615063,0.002523514,0.002394079,0.00221164],"domain_scores_gemma":[0.9815552,0.0111745,0.001717764,0.004399632,0.0004379151,0.0007150068],"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":[0.07336441,0.0001620662,0.002918342,0.0004803959,0.0005450853,0.000386462,0.00504643,0.4818464,0.04540776,0.0003365075,0.389164,0.000342167],"study_design_scores_gemma":[0.003118075,0.000320934,0.02309989,0.005473854,0.0001423124,0.00001572597,0.00077548,0.9540156,0.0008423589,0.00009090247,0.01025672,0.001848216],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3675894,0.01041154,0.4443104,0.03519721,0.01032958,0.0233565,0.08164839,0.006851682,0.02030529],"genre_scores_gemma":[0.9344928,0.00004324278,0.02088362,0.001205196,0.0006093417,0.001107644,0.001458992,0.001089509,0.03910963],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5669034,"threshold_uncertainty_score":0.9998068,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03476743594118432,"score_gpt":0.2806873242925746,"score_spread":0.2459198883513903,"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."}}