{"id":"W4313442501","doi":"10.1016/j.tra.2022.103576","title":"Modeling of low-risk behavior of pedestrian movement based on dynamic data analysis","year":2022,"lang":"en","type":"article","venue":"Transportation Research Part A Policy and Practice","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Pedestrian; Computer science; Transport engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001007661,0.0007956814,0.0009333041,0.0009318046,0.0004410065,0.001276693,0.001203457,0.001059778,0.001273226],"category_scores_gemma":[0.004932344,0.000730908,0.0009609702,0.0007333604,0.0005606859,0.001138422,0.0007392017,0.0010257,0.0002335833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001293656,"about_ca_system_score_gemma":0.001221219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03241855,"about_ca_topic_score_gemma":0.01508914,"domain_scores_codex":[0.9995533,0.000151454,0.00002544327,0.0001376835,0.00006220136,0.00006991487],"domain_scores_gemma":[0.9981451,0.00127976,0.0002341346,0.0000764423,0.0001835819,0.00008094749],"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":[0.00001684747,0.00001752325,0.001480987,0.00001094138,0.00001720179,0.00002647038,0.00001879037,0.9936894,0.0001708358,0.002519994,0.0001248833,0.001906036],"study_design_scores_gemma":[6.116305e-7,0.000002548349,0.0001511073,0.000001115717,0.000002053707,0.000003107598,0.000002592712,0.9992994,0.00002467384,0.000479491,0.00003189715,0.000001377768],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3312722,0.000414764,0.6615782,0.0007566578,0.00008933429,0.0001110145,0.001058811,0.0003791559,0.004339952],"genre_scores_gemma":[0.9810549,0.0002118599,0.01554225,0.0000292634,0.00002672266,0.00006673032,0.0004017413,0.00003231993,0.002634145],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03241855,"threshold_uncertainty_score":0.06445968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.106381196010951,"score_gpt":0.4269619934288892,"score_spread":0.3205807974179382,"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."}}