{"id":"W4385696063","doi":"10.2139/ssrn.4536626","title":"Parameterizing a Pedestrian Agent-Based Model Using an Online Game","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Pedestrian; Computer science; Human–computer interaction; Artificial intelligence; 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":[0.000697549,0.00101887,0.001286652,0.0005843465,0.0007389822,0.001364628,0.001538865,0.002285504,0.003261967],"category_scores_gemma":[0.003056005,0.0008119042,0.0009569246,0.0003635145,0.0009998283,0.001341499,0.001675401,0.001336141,0.0003362096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001174378,"about_ca_system_score_gemma":0.001214787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0220124,"about_ca_topic_score_gemma":0.01114462,"domain_scores_codex":[0.9996972,0.000112865,0.00001123506,0.00006730929,0.00004235253,0.00006916337],"domain_scores_gemma":[0.9988686,0.0006741723,0.0001121153,0.00005238442,0.0001512361,0.0001413448],"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":[0.00002597881,0.0000225921,0.0002545542,0.000006626046,0.000007374891,0.00003285172,0.00001662831,0.9968153,0.0001862976,0.0018924,0.00008411429,0.0006553906],"study_design_scores_gemma":[0.000003328583,0.000004759048,0.00002100866,8.822171e-7,0.000001662126,0.000002586749,0.000002922847,0.9996013,0.00002616863,0.0002991484,0.00003500484,0.000001318139],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2934308,0.0001813704,0.6958699,0.000503531,0.0001560902,0.0001365842,0.0002115595,0.0003030775,0.009207224],"genre_scores_gemma":[0.9758341,0.00006197609,0.01975302,0.00006181365,0.00002500481,0.00008688895,0.00008394559,0.00003655767,0.004056735],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0220124,"threshold_uncertainty_score":0.04376858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0932523269976029,"score_gpt":0.3062359356490073,"score_spread":0.2129836086514044,"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."}}