{"id":"W2709173639","doi":"10.3389/fbioe.2017.00038","title":"Sensitivity Analysis and Accuracy of a CFD-TFM Approach to Bubbling Bed Using Pressure Drop Fluctuations","year":2017,"lang":"en","type":"article","venue":"Frontiers in Bioengineering and Biotechnology","topic":"Granular flow and fluidized beds","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Enerkem (Canada); Université de Sherbrooke","funders":"Ministère de l'Énergie et des Ressources Naturelles; Compute Canada; CRB Innovations; Université de Sherbrooke; Mitacs; Enerkem","keywords":"Pressure drop; Sensitivity (control systems); Computational fluid dynamics; Mechanics; Drop (telecommunication); Environmental science; Computer science; Physics; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002014547,0.0001740277,0.0004227234,0.0008929255,0.0001081928,0.00004233297,0.0001423571,0.0003027335,4.527339e-7],"category_scores_gemma":[0.000146986,0.0001813134,0.00005177893,0.0004617174,0.0001276896,0.000106462,0.0001071387,0.0002192756,1.483319e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002076306,"about_ca_system_score_gemma":0.000006457442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001294323,"about_ca_topic_score_gemma":0.00001594717,"domain_scores_codex":[0.9991941,0.00001277997,0.0002082543,0.0002567804,0.00007303139,0.0002550278],"domain_scores_gemma":[0.9994384,0.00001970824,0.000042977,0.0004155307,0.00002214723,0.00006120381],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002091228,0.00004752425,0.03352939,0.0003929901,0.001079963,0.00001252183,0.0005431746,0.08479622,0.8561381,0.0004966627,0.00006985095,0.02287273],"study_design_scores_gemma":[0.0002826305,0.00001621651,0.01023579,0.00003208978,0.0002520534,0.00001203097,0.00009837328,0.936848,0.05168014,0.00004416434,0.0002770787,0.0002214775],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5332655,0.0008975616,0.4654108,0.00006122278,0.0001295672,0.0001010816,0.00001691788,0.0001004418,0.00001695571],"genre_scores_gemma":[0.9054624,0.0002420902,0.09424171,0.000003235737,0.00001935072,0.000005786935,0.00000545442,0.0000169581,0.000002976786],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8520517,"threshold_uncertainty_score":0.7393745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01009238231623353,"score_gpt":0.2216660075664887,"score_spread":0.2115736252502552,"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."}}