{"id":"W4399931491","doi":"10.1155/2024/6409942","title":"Crowding Perception Thresholds of Passengers in Urban Rail Transit: A Study of Differences in Spatiotemporal Dimensions","year":2024,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Perception; Crowding; Transport engineering; Transit (satellite); Public transport; Rail transit; Economic geography; Computer science; Geography; Psychology; Engineering; Cognitive psychology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001850016,0.00009341126,0.0002542461,0.0004133199,0.00000927871,0.000007003285,0.00005390367,0.0000503541,0.00001256247],"category_scores_gemma":[0.000008721294,0.00008782827,0.00006580417,0.0003867819,0.00001519056,0.0003791263,5.1781e-7,0.0001953018,1.76564e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000564258,"about_ca_system_score_gemma":0.00003070482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001792494,"about_ca_topic_score_gemma":0.001776992,"domain_scores_codex":[0.9988437,0.00002405124,0.0007423635,0.00007783507,0.0002285086,0.0000835497],"domain_scores_gemma":[0.9996849,0.00006603443,0.0001055624,0.00005331389,0.00006303379,0.00002715927],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001203686,0.0002451761,0.1571218,0.0003702886,0.00004771455,0.00004204493,0.05779993,0.710852,0.07036045,0.0001906296,0.00000385934,0.002845711],"study_design_scores_gemma":[0.001381915,0.0003157398,0.9626892,0.0006002085,0.00004316581,0.0000021116,0.01350525,0.02046485,0.0006563638,0.0002380499,0.000003518145,0.00009964507],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947429,0.000310877,0.004516446,0.00002500012,0.000214814,0.0001484195,0.000006942787,0.00001592036,0.00001872755],"genre_scores_gemma":[0.9989623,0.0002845597,0.0007085153,0.000001806106,0.000015155,0.000003355146,0.000007721928,0.00001363605,0.00000299601],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8055674,"threshold_uncertainty_score":0.3581533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01310687640273327,"score_gpt":0.2549395907146683,"score_spread":0.241832714311935,"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."}}