{"id":"W2100884632","doi":"10.5539/mas.v3n9p95","title":"The Performance Study of Hybrid-driving Differential Gear Trains","year":2009,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Iterative Learning Control Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Differential (mechanical device); Computer science; Train; Gear train; Test bench; Encoder; Control theory (sociology); Mechanism (biology); Controller (irrigation); Variable (mathematics); Automotive engineering; Control engineering; Engineering; Control (management); Mathematics; Artificial intelligence; Physics; Embedded system","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003896211,0.0001158191,0.0001478448,0.00006791193,0.00038479,0.0001170071,0.0004993962,0.00001183226,0.000002386771],"category_scores_gemma":[0.00001236704,0.00008334142,0.00002036898,0.0002226204,0.0001243832,0.0001166897,0.0000305144,0.0001575062,0.00000828202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005075901,"about_ca_system_score_gemma":0.00001821699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001679162,"about_ca_topic_score_gemma":0.000004545039,"domain_scores_codex":[0.998809,0.00001591029,0.0002079414,0.0002021038,0.0004448711,0.0003201324],"domain_scores_gemma":[0.9995328,0.00003671305,0.00004408829,0.000302913,0.00003605022,0.00004747256],"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":[0.000007719483,0.00005588401,0.0007263302,0.000007194505,0.000008919813,0.000001025866,0.005721257,0.07449887,0.8881077,0.0003226164,0.0000120966,0.03053045],"study_design_scores_gemma":[0.0003330625,0.00008867178,0.03824916,0.000008477382,0.000004163438,0.000001818219,0.0001989723,0.9523767,0.008538277,0.00005205744,0.00004461029,0.000104088],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9474854,0.00001923648,0.04901036,0.00001205999,0.0001382872,0.0003118778,3.858763e-7,0.0001090131,0.002913344],"genre_scores_gemma":[0.9998114,0.000001734627,0.00004496563,0.000007462163,0.00005046253,0.00001712362,1.751659e-7,0.000009411819,0.00005728464],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8795694,"threshold_uncertainty_score":0.3398564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007180698560249861,"score_gpt":0.2076864978169209,"score_spread":0.2005057992566711,"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."}}