{"id":"W625169584","doi":"","title":"DELIVERING COMMUTER TRAIN: WHERE SMART TRANSPORT AND ENERGY PLANNING MEET","year":2011,"lang":"en","type":"article","venue":"CONGRESS - DUBAI 2011","topic":"Railway Systems and Energy Efficiency","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transport engineering; Computer science; Energy (signal processing); Engineering; Physics","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":[0.0001113887,0.0002383877,0.0002659892,0.00008845054,0.0001072515,0.00002377751,0.0002054271,0.0001316662,0.00032274],"category_scores_gemma":[0.00000178753,0.000228343,0.00006047028,0.00005689624,0.00008128006,0.0002038907,0.00002538505,0.000106851,0.00001751045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001718924,"about_ca_system_score_gemma":0.000009362136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001125078,"about_ca_topic_score_gemma":0.0004747492,"domain_scores_codex":[0.9989973,0.00002021335,0.0002749421,0.0002244322,0.0001214669,0.0003615972],"domain_scores_gemma":[0.9994759,0.00001948975,0.00003553626,0.0002836001,0.00003110904,0.0001543612],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000502527,0.0007494448,0.4544547,0.003529729,0.00267663,0.004219164,0.09815201,0.06605872,0.02283865,0.07358848,0.0757093,0.1975206],"study_design_scores_gemma":[0.004734857,0.0005989793,0.2434527,0.002018967,0.0003252413,0.0006326965,0.001849293,0.1447032,0.01424495,0.0004905757,0.5821733,0.004775272],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8825767,0.007373107,0.006365733,0.00001799085,0.001736572,0.00007735097,0.00002344223,0.0005321899,0.1012969],"genre_scores_gemma":[0.9985749,0.0001907037,0.0003540244,0.00003351246,0.0000882769,0.00002454578,0.000007494408,0.0000553642,0.0006711531],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.506464,"threshold_uncertainty_score":0.9311556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02124281131158277,"score_gpt":0.1881039681645759,"score_spread":0.1668611568529931,"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."}}