{"id":"W2972813637","doi":"10.1115/1.4044531","title":"Computational Fluid Dynamics Modeling of Fire and Human Evacuation for Nuclear Applications","year":2019,"lang":"en","type":"article","venue":"Journal of Nuclear Engineering and Radiation Science","topic":"Fire dynamics and safety research","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nuclear Laboratories","funders":"","keywords":"Computational fluid dynamics; Computer science; Large eddy simulation; High fidelity; Fidelity; Fire Dynamics Simulator; Environmental science; Simulation; Nuclear engineering; Marine engineering; Aerospace engineering; Engineering; Meteorology; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002261357,0.0003871124,0.000324314,0.0003465931,0.000610031,0.0006531763,0.0004892999,0.0007688895,0.001493281],"category_scores_gemma":[0.0006989267,0.0002070002,0.0004928925,0.0002318809,0.000566246,0.0003550749,0.0005261199,0.0004896722,0.0001810604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008568979,"about_ca_system_score_gemma":0.001557007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04664371,"about_ca_topic_score_gemma":0.02299051,"domain_scores_codex":[0.9999034,0.0000284006,0.000003435141,0.0000118738,0.00003547053,0.00001724702],"domain_scores_gemma":[0.9997987,0.0001041533,0.00002393259,0.00001265552,0.00003941721,0.00002110976],"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":[0.00002410726,0.0000170073,0.0009041644,0.0000102216,0.000005352299,0.00005712642,0.00002549516,0.9938022,0.001525556,0.001348553,0.0002368355,0.002043397],"study_design_scores_gemma":[0.000003130094,0.000005255781,0.0002324146,0.000001549829,9.808765e-7,0.000005539323,0.000007312284,0.9990082,0.0002599712,0.0001761639,0.0002973722,0.000002099609],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.656346,0.0006257943,0.3091601,0.001076529,0.0002397873,0.0001681076,0.0007369898,0.0006597558,0.03098695],"genre_scores_gemma":[0.9824501,0.0001760634,0.01346231,0.00004445618,0.00002272803,0.00004752648,0.0001359952,0.00003310591,0.003627841],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04664371,"threshold_uncertainty_score":0.09274441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007048998403791188,"score_gpt":0.2408504517480888,"score_spread":0.2338014533442976,"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."}}