{"id":"W2362918992","doi":"","title":"Advantages and Application of Linear Induction Motor in Urban Transit System","year":2008,"lang":"en","type":"article","venue":"Converter Technology & Electric Traction","topic":"Railway Systems and Energy Efficiency","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bogie; Linear induction motor; Urban rail transit; Urban rail; Urban transit; Linear motor; Automotive engineering; Traction motor; Rail transit; Transport engineering; Engineering; Transit system; Traction (geology); Transit (satellite); Induction motor; Public transport; Mechanical engineering; Electrical engineering; Voltage","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001360841,0.000150341,0.00008488143,0.0003622556,0.0002072666,0.0002891085,0.0001844304,0.000191853,0.003179399],"category_scores_gemma":[0.0001573569,0.00007471437,0.0001235541,0.000358896,0.0001375216,0.0003506055,0.0003102018,0.0001590012,0.000659934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002330145,"about_ca_system_score_gemma":0.0001943499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001564654,"about_ca_topic_score_gemma":0.001379273,"domain_scores_codex":[0.9998676,0.00002736772,0.000007200658,0.00001913116,0.00005984584,0.00001889445],"domain_scores_gemma":[0.9999205,0.00001420064,0.000008918866,0.00000821147,0.00004024649,0.000007915132],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007322093,0.0001125711,0.01932736,0.0007666606,0.00003910611,0.002955135,0.0007906493,0.02884977,0.2017919,0.05012682,0.01013359,0.6843743],"study_design_scores_gemma":[0.0001254228,0.001476053,0.03990355,0.0002461879,0.0002030393,0.0107166,0.001237332,0.2547769,0.1270031,0.02259471,0.5415536,0.0001634612],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3870955,0.01192539,0.2965859,0.001916013,0.0003148668,0.0001084834,0.0002451781,0.003028595,0.2987801],"genre_scores_gemma":[0.964752,0.002923306,0.01563852,0.0001084863,0.0001713948,0.00001876642,0.00008104886,0.00004180849,0.01626484],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003179399,"threshold_uncertainty_score":0.01063615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003909506238337504,"score_gpt":0.1807727491270489,"score_spread":0.1768632428887114,"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."}}