{"id":"W4401128463","doi":"10.1002/cjce.25435","title":"Parameter sensitivity of a wood chips flow model","year":2024,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Granular flow and fluidized beds","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Energimyndigheten","keywords":"Computational fluid dynamics; Mechanics; Materials science; Volume fraction; Sensitivity (control systems); Oscillation (cell signaling); Flow (mathematics); Permeability (electromagnetism); Viscosity; Composite material; Chemistry; Engineering; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005911579,0.0005886133,0.0006274343,0.000588813,0.0003486465,0.001099223,0.0006212732,0.00120858,0.001313822],"category_scores_gemma":[0.002773346,0.0003314312,0.000599072,0.0002835601,0.0007701042,0.0006006852,0.0005332952,0.0008270607,0.000178423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006855711,"about_ca_system_score_gemma":0.0007715218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01537697,"about_ca_topic_score_gemma":0.003514159,"domain_scores_codex":[0.9996455,0.0001234056,0.00001727702,0.00006619923,0.00007721529,0.00007035839],"domain_scores_gemma":[0.9984794,0.001089228,0.0001177432,0.0001043229,0.0001592833,0.00005005599],"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":[0.00003765842,0.00001799032,0.0005518239,0.000009477691,0.000009054301,0.00003386898,0.00001167513,0.9961941,0.001975023,0.0005054979,0.00004921529,0.0006045672],"study_design_scores_gemma":[0.00000369279,0.00001645945,0.0002167348,0.000002442378,0.000003004597,0.000004576996,0.000005458038,0.9982548,0.001291749,0.0001188969,0.00007808372,0.000004001641],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9325718,0.0001928186,0.05709211,0.000225045,0.00004464608,0.00009015601,0.000339905,0.0002671797,0.00917629],"genre_scores_gemma":[0.9971317,0.00004619428,0.001882223,0.00002529054,0.000003378793,0.00002449035,0.0001192812,0.00001821305,0.0007491643],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01537697,"threshold_uncertainty_score":0.03057498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008747800196123819,"score_gpt":0.1760780522743347,"score_spread":0.1673302520782109,"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."}}