{"id":"W4388092559","doi":"10.48550/arxiv.2310.18480","title":"Capacity, Collision Avoidance and Shopping Rate under a Social Distancing Regime","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Slowdown; Baseline (sea); Social distance; Trajectory; Computer science; Econometrics; Simulation; Economics; Coronavirus disease 2019 (COVID-19); Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007705395,0.0002930919,0.0004478835,0.0005793704,0.0006000664,0.001287515,0.0007574896,0.0009406252,0.002432347],"category_scores_gemma":[0.005605192,0.000233927,0.0005667145,0.0003634303,0.001763922,0.001897303,0.001148107,0.0008240278,0.0002098815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001170576,"about_ca_system_score_gemma":0.0006325988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005017699,"about_ca_topic_score_gemma":0.002009212,"domain_scores_codex":[0.9996995,0.00009171892,0.000009509346,0.00005240056,0.00003787161,0.000109034],"domain_scores_gemma":[0.9972858,0.001249487,0.0006901559,0.0002114887,0.0001900584,0.0003729968],"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":[0.0003018896,0.0001568275,0.01222937,0.00006296563,0.00006468185,0.0005346156,0.0004695614,0.7774937,0.009694612,0.1917307,0.001288231,0.005972853],"study_design_scores_gemma":[0.00002457188,0.0001242811,0.005297342,0.00001541598,0.0000197476,0.0001316466,0.0002237868,0.9451274,0.000970729,0.04760455,0.0004245861,0.00003594075],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9504954,0.0001316464,0.04086661,0.0006654712,0.00001782538,0.00002012307,0.0001139911,0.00006289361,0.007626115],"genre_scores_gemma":[0.9978887,0.00004527428,0.001130653,0.00001801147,0.000006533054,0.00001033511,0.00002021302,0.000009946501,0.0008702676],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005017699,"threshold_uncertainty_score":0.009976983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1879243687625048,"score_gpt":0.1841262966925565,"score_spread":0.003798072069948366,"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."}}