{"id":"W2618304992","doi":"10.1002/cav.1783","title":"On density–flow relationships during crowd evacuation","year":2017,"lang":"en","type":"article","venue":"Computer Animation and Virtual Worlds","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; York University","funders":"","keywords":"Crowds; Computer science; Generality; Crowd simulation; Pedestrian; Relation (database); Variety (cybernetics); Data mining; Synthetic data; Machine learning; Artificial intelligence; Computer security; Transport 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":[0.001827274,0.0004098823,0.0003073426,0.001490973,0.0005156298,0.0007423571,0.0004656037,0.0005902911,0.00104957],"category_scores_gemma":[0.01908633,0.0003405379,0.000224438,0.0007210054,0.001056096,0.001529655,0.0008792363,0.0005268719,0.0001029934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001048004,"about_ca_system_score_gemma":0.0004729764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01112993,"about_ca_topic_score_gemma":0.006392066,"domain_scores_codex":[0.9993349,0.0003231523,0.00003078962,0.0001062975,0.0001055059,0.00009936763],"domain_scores_gemma":[0.9921496,0.005498653,0.001029993,0.0002786376,0.0008449169,0.0001981165],"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":[0.0001501197,0.00007460715,0.02789854,0.0000546633,0.00003228935,0.0001169109,0.0002292823,0.9565115,0.002208071,0.005090294,0.0005995519,0.007034085],"study_design_scores_gemma":[0.00000731038,0.00004414509,0.01246753,0.00001362314,0.000007157877,0.00004156308,0.0002580185,0.9813886,0.001869494,0.003479369,0.0004024517,0.00002073093],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9448418,0.000174581,0.05168397,0.0003304555,0.00001596626,0.00004833424,0.0003452286,0.0001167576,0.002442785],"genre_scores_gemma":[0.9977876,0.00003721823,0.001872243,0.00001038913,0.000004385201,0.0000111727,0.000126297,0.000009658568,0.0001410939],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01112993,"threshold_uncertainty_score":0.02213025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01903133193288933,"score_gpt":0.2389441185141239,"score_spread":0.2199127865812345,"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."}}