{"id":"W568498514","doi":"","title":"LSTAR: A New Way of Moving for Central and South Texas","year":2011,"lang":"en","type":"article","venue":"Mass transit","topic":"Transport and Economic Policies","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Train; Transport engineering; Service (business); Mile; Traffic congestion; Rail transportation; Geography; Engineering; Business; Archaeology; Marketing","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":[0.00006137178,0.00009779941,0.0001623989,0.00007386479,0.00004061743,0.00003058112,0.00008769547,0.00003829293,0.0001601349],"category_scores_gemma":[0.00000277915,0.00009284949,0.00006880673,0.00004950638,0.00003424575,0.0003187367,0.000006456124,0.00003320051,0.00001316447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004313785,"about_ca_system_score_gemma":0.000009343778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001359815,"about_ca_topic_score_gemma":0.0002433503,"domain_scores_codex":[0.9994286,7.709469e-7,0.0001675112,0.0001288226,0.00003692452,0.000237379],"domain_scores_gemma":[0.9998205,0.000006228874,0.00005882583,0.00008374087,0.00001393684,0.00001675807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008006941,0.0001406921,0.8203912,0.001941168,0.000292618,0.00001218424,0.01370938,0.0001734205,0.003299599,0.1362436,0.00254793,0.0204475],"study_design_scores_gemma":[0.003549697,0.00004331599,0.9146344,0.0001030981,0.000377157,0.000001444152,0.0009842768,0.002668391,0.002506566,0.02091177,0.05355949,0.000660389],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9708751,0.00007927309,0.01129796,0.000245196,0.0001684901,0.0002019383,0.00001346489,0.00005671618,0.01706182],"genre_scores_gemma":[0.998333,0.000003178793,0.0007720033,0.0002489788,0.00027959,0.00000255566,0.000007966478,0.00001545394,0.0003373126],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1153319,"threshold_uncertainty_score":0.3786292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02889384760793355,"score_gpt":0.1800500025364626,"score_spread":0.1511561549285291,"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."}}