{"id":"W4393276688","doi":"10.4038/jsalt.v4i1.90","title":"An Agent-Based Crowd Dynamics Simulation that Considers Idling and Time-and-Distance-Conscious Optimising Behaviour","year":2024,"lang":"en","type":"article","venue":"Journal of South Asian Logistics and Transport","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Calgary","funders":"","keywords":"Dynamics (music); Crowd simulation; Computer science; Simulation; Psychology; Crowds; Computer security","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":[0.000360726,0.0004669524,0.0006927638,0.0004876902,0.0006531909,0.0008925697,0.0008292525,0.001209658,0.002411799],"category_scores_gemma":[0.001498212,0.0002854929,0.0006324939,0.0004662646,0.0005290507,0.0006732608,0.001040829,0.0007299641,0.0002258737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007872063,"about_ca_system_score_gemma":0.001455924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02220161,"about_ca_topic_score_gemma":0.01505898,"domain_scores_codex":[0.9998701,0.00004869966,0.000006334777,0.00002095901,0.00002589611,0.00002811467],"domain_scores_gemma":[0.9992967,0.000403523,0.00006249968,0.00004043673,0.0000785177,0.0001182663],"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":[0.00007002201,0.00007861375,0.002152473,0.00003326202,0.00003071473,0.00008550875,0.00009489783,0.9909508,0.0005232356,0.003403441,0.0003260665,0.002250913],"study_design_scores_gemma":[0.00002034574,0.00003426163,0.0002336726,0.000005600838,0.000008023711,0.000009922466,0.00003226123,0.9982249,0.0001146732,0.0006415622,0.0006674067,0.000007343519],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8130246,0.0002780773,0.1549853,0.0007679603,0.0002066562,0.0003486011,0.001066856,0.0005460679,0.02877585],"genre_scores_gemma":[0.95648,0.0001893702,0.03896867,0.00008736832,0.0000181774,0.0002643921,0.0004076604,0.0000416222,0.003542792],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02220161,"threshold_uncertainty_score":0.04414475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01598610169360965,"score_gpt":0.2476558594061665,"score_spread":0.2316697577125568,"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."}}