{"id":"W2599226259","doi":"10.1002/cav.1749","title":"CODE: Crowd‐optimized design of environments","year":2017,"lang":"en","type":"article","venue":"Computer Animation and Virtual Worlds","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick; University of British Columbia; York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Modular design; Code (set theory); Crowd simulation; Aggregate (composite); Design flow; Human–computer interaction; Embedded system; Programming language; Crowds","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006568012,0.0008264769,0.0004685703,0.0005383488,0.0006281724,0.0009683768,0.001339116,0.0006928351,0.005846495],"category_scores_gemma":[0.002595965,0.0005248402,0.0005280969,0.0002225733,0.0009658888,0.0008650079,0.001765583,0.0007420307,0.001044412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005752931,"about_ca_system_score_gemma":0.001227036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002168507,"about_ca_topic_score_gemma":0.002441259,"domain_scores_codex":[0.9994639,0.0001345618,0.00002256595,0.00007736452,0.000241426,0.0000603202],"domain_scores_gemma":[0.9991672,0.0003034786,0.00007196249,0.0001563463,0.0002207231,0.00008036039],"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":[0.00009970577,0.00005087191,0.001597897,0.0001328004,0.00003261722,0.0001348687,0.0002311352,0.9265203,0.01236465,0.01675729,0.005541706,0.03653625],"study_design_scores_gemma":[0.00002813003,0.00003261467,0.0001783276,0.00001759332,0.000009686155,0.00003802205,0.00003235555,0.9746643,0.006301336,0.00461135,0.01406742,0.00001889181],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03790608,0.0001421909,0.9389468,0.0002117392,0.0001012849,0.000135131,0.0002562919,0.009419063,0.01288136],"genre_scores_gemma":[0.561413,0.0002338598,0.4287802,0.0001993615,0.00003076157,0.0003923026,0.0005070176,0.002507005,0.005936464],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005846495,"threshold_uncertainty_score":0.01955849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02164110309028684,"score_gpt":0.2448238321768636,"score_spread":0.2231827290865768,"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."}}