{"id":"W621268125","doi":"","title":"CANADIAN GOVERNMENT STUDYING TRANSIT FUNDING ROLE, TRIGGERING INDUSTRY OPTIMISM","year":2001,"lang":"en","type":"article","venue":"Passenger transport","topic":"Corruption and Economic Development","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Optimism; Transit (satellite); Government (linguistics); Business; Urban transit; Rapid transit; Rail transit; Transport engineering; Public transport; Engineering; Psychology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000779302,0.0001487459,0.000187913,0.00008489298,0.0005911402,0.00006386841,0.0002054263,0.0002079601,0.003188947],"category_scores_gemma":[0.0000100868,0.0001747623,0.00008448333,0.0002278652,0.00003955616,0.0002209669,0.0000048918,0.0003176444,0.00009076988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001370263,"about_ca_system_score_gemma":0.0005202981,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.09370688,"about_ca_topic_score_gemma":0.4929546,"domain_scores_codex":[0.9983584,0.00003512923,0.0003062049,0.0002907569,0.0003657967,0.0006436809],"domain_scores_gemma":[0.9991938,0.00002953771,0.00004746303,0.0001341943,0.00002159227,0.0005733414],"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":[0.00004853537,0.0001503608,0.724575,0.00001978647,0.0001643047,0.0003481219,0.06857035,0.001289751,0.0002711746,0.002492777,0.0002325852,0.2018372],"study_design_scores_gemma":[0.0003502302,0.00001056808,0.1899171,0.00003397618,0.00003025968,0.000005419964,0.02255897,0.00007616463,0.00003277119,0.0000285902,0.7865723,0.0003837289],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.764098,0.000059869,0.0002323172,0.003323789,0.0005138472,0.0002429833,0.000009698206,0.00008876816,0.2314307],"genre_scores_gemma":[0.9899782,0.0002114679,0.000207796,0.0003552449,0.0001965774,0.00003170634,0.000006090612,0.00001854589,0.008994396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7863397,"threshold_uncertainty_score":0.9977223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0384655691430001,"score_gpt":0.2675730595905418,"score_spread":0.2291074904475417,"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."}}