{"id":"W2321174942","doi":"10.1061/9780784479797.024","title":"The Detroit People Mover with a Canadian Connection","year":2016,"lang":"en","type":"article","venue":"","topic":"Underground infrastructure and sustainability","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Downtown; Light rail transit; Government (linguistics); Corporation; Public transport; Light rail; Transit system; Transit (satellite); Transport engineering; Engineering; Urban rail; Business; Geography; Finance; Archaeology","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":[0.00004703966,0.00005415002,0.00004142683,0.00002007314,0.0001028784,0.00002902726,0.00005058137,0.00002650511,0.0002905382],"category_scores_gemma":[0.00001734082,0.00002285795,0.00001234907,0.00007229329,0.00002002578,0.00009517186,0.000003202445,0.00003441378,0.00001692654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002495823,"about_ca_system_score_gemma":0.00005423261,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02141202,"about_ca_topic_score_gemma":0.7032958,"domain_scores_codex":[0.9996455,0.000005739414,0.00004953643,0.00005926145,0.00005154863,0.0001883734],"domain_scores_gemma":[0.9996969,0.00005288344,0.000003792957,0.0001393447,0.00003355595,0.00007349038],"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":[0.0001171653,0.00002733668,0.4446332,0.0001106445,0.0005077636,0.00002406768,0.001742776,0.003486638,0.00415563,0.2360464,0.1288314,0.180317],"study_design_scores_gemma":[0.001043134,0.0001817979,0.4425455,0.00001728285,0.00002764835,0.00004540576,0.002143159,0.0041183,0.003517889,0.04263541,0.503127,0.000597489],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8402781,0.00003434309,0.02917814,0.001735057,0.0001772539,0.0001557768,0.000002603728,0.0001943222,0.1282444],"genre_scores_gemma":[0.9977363,0.000007377731,0.00008390174,0.00006637663,0.00003216097,0.000007911531,3.120436e-7,0.000008223247,0.002057455],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6818838,"threshold_uncertainty_score":0.9851045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.001544942124335499,"score_gpt":0.1447917343401403,"score_spread":0.1432467922158048,"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."}}