{"id":"W4235105819","doi":"10.32920/ryerson.14657025","title":"Prediction Of Particle Laden Flow In Gas Pipe","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Particle Dynamics in Fluid Flows","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Turbulence; Mechanics; Two-phase flow; Particle (ecology); Flow (mathematics); Eddy; Dispersion (optics); Particle size; Particle number; Natural gas; Materials science; Physics; Chemistry; Geology; Thermodynamics; Volume (thermodynamics); Optics","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":[0.0002988444,0.0004524491,0.0003737989,0.0004289193,0.0003407248,0.000646001,0.0003851552,0.001105102,0.0005930572],"category_scores_gemma":[0.0008436454,0.0002797812,0.0003432072,0.0002287002,0.0007352225,0.0004020229,0.0003108134,0.0003312366,0.00008446463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008154021,"about_ca_system_score_gemma":0.00079109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0116465,"about_ca_topic_score_gemma":0.003094086,"domain_scores_codex":[0.9999225,0.00001931061,0.000003099617,0.00001712542,0.00002136687,0.00001662732],"domain_scores_gemma":[0.9997047,0.0001715025,0.00005080141,0.000007737559,0.00003623889,0.00002905862],"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":[0.00004011044,0.00002049293,0.001153463,0.00001229932,0.000003917723,0.00004665574,0.00001488669,0.9952685,0.001861621,0.000574925,0.00003384635,0.000969239],"study_design_scores_gemma":[0.000003034089,0.000009436834,0.0001434338,4.841333e-7,5.078035e-7,0.000002162531,0.000002145899,0.9995161,0.0002174174,0.0000846543,0.0000196493,9.758185e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8773051,0.0001933353,0.1195988,0.0001461406,0.00003626397,0.0000515359,0.0001182334,0.0002797068,0.002270883],"genre_scores_gemma":[0.9915925,0.00006161636,0.007126041,0.00000927251,0.000006030488,0.00001883044,0.00005645517,0.00001701551,0.001112211],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0116465,"threshold_uncertainty_score":0.02315742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02172063887946942,"score_gpt":0.2202366540647011,"score_spread":0.1985160151852317,"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."}}