{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006077626,0.000102444,0.0001822091,0.0005463813,0.00004533736,0.000001981473,0.00006136434,0.0002465768,9.000651e-7],"category_scores_gemma":[0.000004118369,0.0001072821,0.00002154346,0.0006104764,0.0000364436,0.000129493,0.000002909585,0.0001949845,0.000004626321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009056844,"about_ca_system_score_gemma":0.000009726239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006788818,"about_ca_topic_score_gemma":0.000009197658,"domain_scores_codex":[0.9993563,0.00001108537,0.0002509561,0.0001648816,0.00006738083,0.0001494311],"domain_scores_gemma":[0.9997526,0.00001130487,0.0000498024,0.0001411287,0.00002667535,0.00001841849],"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":[0.00002425075,0.00005891443,0.009748881,0.0001847781,0.00002679895,0.000007447949,0.000306625,0.001642375,0.871101,0.0007420317,0.00003589899,0.116121],"study_design_scores_gemma":[0.0008788893,0.0002900605,0.04297841,0.00005895151,0.00003005966,0.0006660382,0.0004232117,0.7837463,0.1691112,0.00003181713,0.001476127,0.0003089209],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9384445,0.0008678,0.05974642,0.00003153334,0.0001530427,0.0001801853,8.175645e-7,0.0004206473,0.0001550666],"genre_scores_gemma":[0.9995285,0.0002206844,0.0001132574,0.000001943637,0.00003536869,0.00006104154,0.000002690329,0.00001549549,0.0000210739],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.782104,"threshold_uncertainty_score":0.4374836,"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."}}