{"id":"W3092544424","doi":"10.17816/transsyst20206331-42","title":"A Maglev, a tunnel, a river. On the delays in the realization of the Tokyo-Nagoya Maglev line","year":2020,"lang":"en","type":"article","venue":"Transportation systems and technology","topic":"Mobile Agent-Based Network Management","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"International Air Transport Association","funders":"","keywords":"Maglev; Line (geometry); Section (typography); Realization (probability); Engineering; Computer science; Electrical engineering; Mathematics; Geometry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005979711,0.0003093923,0.0001638408,0.0003274703,0.002274597,0.004474963,0.0002823664,0.001983587,0.01076819],"category_scores_gemma":[0.0008178705,0.000199795,0.0001936054,0.0006911713,0.00117642,0.00263528,0.001351078,0.001501814,0.001737512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002517623,"about_ca_system_score_gemma":0.002970451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01918967,"about_ca_topic_score_gemma":0.05393105,"domain_scores_codex":[0.9996189,0.0001005833,0.0000145372,0.00005971319,0.0001250215,0.00008124913],"domain_scores_gemma":[0.9997037,0.00004486789,0.00004605639,0.00001534444,0.00009015442,0.0001000007],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0005416395,0.0000777288,0.006889928,0.000613306,0.00004854667,0.003378894,0.005342719,0.004029273,0.01038433,0.5574542,0.1470909,0.2641485],"study_design_scores_gemma":[0.00001695696,0.0001343435,0.005375057,0.00018803,0.0000192437,0.0005501327,0.006062478,0.0008024886,0.0009213191,0.0199238,0.9659639,0.00004226451],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1472067,0.06956322,0.02824612,0.1208995,0.008589023,0.0001044548,0.0003467439,0.0005005808,0.6245437],"genre_scores_gemma":[0.7330747,0.01989247,0.008413274,0.004501605,0.0007272376,0.0000391615,0.0001918659,0.00008303164,0.2330765],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01918967,"threshold_uncertainty_score":0.03815591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02216525080054561,"score_gpt":0.2086683388196207,"score_spread":0.1865030880190751,"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."}}