{"id":"W3013711141","doi":"10.1016/j.tra.2020.03.020","title":"Weather, travel mode choice, and impacts on subway ridership in Beijing","year":2020,"lang":"en","type":"article","venue":"Transportation Research Part A Policy and Practice","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":130,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"China Scholarship Council; National Natural Science Foundation of China","keywords":"Beijing; Recreation; Transport engineering; Environmental science; Adverse weather; Meteorology; Geography; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00236009,0.0001148243,0.000169775,0.0001565033,0.0004501762,0.00013932,0.000130591,0.0001156831,0.00009820839],"category_scores_gemma":[0.002770309,0.0001123273,0.00003025033,0.0008017072,0.0003575627,0.001031924,0.00000327196,0.0005417023,0.00001036693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004413863,"about_ca_system_score_gemma":0.0003706652,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0354274,"about_ca_topic_score_gemma":0.04146111,"domain_scores_codex":[0.9975695,0.0006903784,0.0002672359,0.0003597497,0.0006094368,0.0005036779],"domain_scores_gemma":[0.9966269,0.002652943,0.00006919556,0.0001012304,0.00011611,0.0004336109],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001851997,0.0004318323,0.6496557,0.000301922,0.00005824687,0.00006810737,0.2255509,0.00006303971,0.0008668297,0.1128901,0.001235844,0.0070255],"study_design_scores_gemma":[0.001215547,0.0002711656,0.8782057,0.00008319792,0.00002537803,2.26732e-7,0.01394721,0.0001440419,0.0001331684,0.001895479,0.1038314,0.0002474636],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.913537,0.000243871,0.00004212103,0.06461881,0.00002098282,0.0004540234,0.00004528638,0.00003531118,0.0210026],"genre_scores_gemma":[0.9967774,0.001167174,0.00005942281,0.001308835,0.0003304105,0.00002399174,0.00001826179,0.00001185931,0.0003026719],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.22855,"threshold_uncertainty_score":0.9760298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2389846138186854,"score_gpt":0.4980136923236264,"score_spread":0.2590290785049409,"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."}}