{"id":"W415705","doi":"10.1001/archneur.1978.00500270003001","title":"A Bi-Modal Microsimulation Tool for the Assessment of Pedestrian Delays and Traffic Management 1","year":2000,"lang":"en","type":"article","venue":"Archives of Neurology","topic":"Traffic control and management","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Microsimulation; Pedestrian; Modal; Computer science; Transport engineering; Engineering","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":[0.00005230621,0.00007315813,0.000118508,0.00005549998,0.00002775843,0.00000464027,0.00009477577,0.0000164331,0.00001292016],"category_scores_gemma":[0.000001595387,0.00005883568,0.00004816859,0.00003124216,0.00005683357,0.00001908978,0.00001984275,0.00004651109,3.352638e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001467008,"about_ca_system_score_gemma":0.00000299767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000305982,"about_ca_topic_score_gemma":0.00001498944,"domain_scores_codex":[0.9995285,0.00001903591,0.000170606,0.0001066097,0.00004243882,0.0001327621],"domain_scores_gemma":[0.9995713,0.0002551734,0.00002340931,0.0001321127,0.000003137232,0.00001491694],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009778231,0.000030316,0.0001865648,0.0001049147,0.00008074441,0.000001446933,0.0001283599,0.5612745,0.00105704,0.0009790135,0.00005485763,0.4360044],"study_design_scores_gemma":[0.001478479,0.0002921237,0.285469,0.000005375401,0.00008034029,0.000002799569,0.00001143874,0.6977229,0.00002274721,0.0003552013,0.01449101,0.0000686392],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9871789,0.0001384977,0.01002033,0.0004904043,0.0000712964,0.0005200492,0.0000117932,0.00003938494,0.001529398],"genre_scores_gemma":[0.9982246,0.0003544579,0.001243902,0.00006214421,0.00001791449,0.00004050451,0.000003827815,0.000009495409,0.00004321702],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4359358,"threshold_uncertainty_score":0.2399249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006341937352968471,"score_gpt":0.2204447421847245,"score_spread":0.214102804831756,"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."}}