{"id":"W4234736284","doi":"10.32920/ryerson.14650080.v1","title":"Computational modeling of fire safety in metro-stations","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"National Institute of Standards and Technology; Teknologian Tutkimuskeskus VTT","keywords":"Computational fluid dynamics; Pathfinder; Smoke; Fire Dynamics Simulator; Fire safety; Computer science; Environmental science; Marine engineering; Simulation; Engineering; Civil engineering; Aerospace 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":[0.0002143369,0.0005187411,0.0004718832,0.000373137,0.0007169204,0.001365687,0.00103608,0.0009899286,0.002940385],"category_scores_gemma":[0.0008722341,0.0002711014,0.0005443922,0.0004426668,0.0007124226,0.0006958974,0.001041236,0.0005391432,0.0004447419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008565909,"about_ca_system_score_gemma":0.00111235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01605745,"about_ca_topic_score_gemma":0.007901818,"domain_scores_codex":[0.9998087,0.00003891441,0.000008977311,0.00003827396,0.00006596456,0.00003920331],"domain_scores_gemma":[0.9997982,0.00008267223,0.0000323049,0.00002541262,0.00003800745,0.00002335955],"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":[0.00001669914,0.00001114683,0.0004439421,0.000009508206,0.000005192142,0.00004347451,0.0000352502,0.992397,0.0005472396,0.004921081,0.0001337557,0.001435676],"study_design_scores_gemma":[0.000003782061,0.000007504353,0.0001729814,0.000003916362,0.000002263128,0.000009068506,0.00002536209,0.9972435,0.0002360318,0.001395696,0.0008967075,0.000003099058],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4669442,0.0006070453,0.4487384,0.0008042926,0.0001739412,0.0001382393,0.001022517,0.0005140006,0.08105741],"genre_scores_gemma":[0.9621437,0.0004170506,0.02261894,0.00004488957,0.00003565541,0.00009217842,0.000368101,0.00006948524,0.01420998],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01605745,"threshold_uncertainty_score":0.031928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01841554786673893,"score_gpt":0.2547724727548936,"score_spread":0.2363569248881547,"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."}}