{"id":"W4414920343","doi":"10.1016/j.mineng.2025.109812","title":"Wet screen performance prediction using coupled DEM and SPH: separation, wear and comparison to plant measurement","year":2025,"lang":"en","type":"article","venue":"Minerals Engineering","topic":"Granular flow and fluidized beds","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Goldcorp","keywords":"Slurry; Volumetric flow rate; Flow (mathematics); Abrasion (mechanical); Mass flow rate; Scale model; Scale (ratio); Fraction (chemistry)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0002587551,0.0005875942,0.0005232068,0.0003937343,0.0002196124,0.000583316,0.0007189,0.0007051586,0.001418729],"category_scores_gemma":[0.0008964019,0.0002460775,0.0005025553,0.0004639952,0.0003116225,0.0003881682,0.000387123,0.0004225903,0.0002967714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005725651,"about_ca_system_score_gemma":0.0004476163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01240734,"about_ca_topic_score_gemma":0.007073434,"domain_scores_codex":[0.9998851,0.00001537376,0.000008705291,0.00001889722,0.00005447848,0.00001750356],"domain_scores_gemma":[0.9994932,0.0002324853,0.00004565534,0.00008047866,0.0001076866,0.00004044048],"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":[0.0002840135,0.00020554,0.02150136,0.0002093479,0.00004313786,0.0003091054,0.0001308367,0.9215279,0.03421778,0.000471369,0.0006543035,0.02044527],"study_design_scores_gemma":[0.00002154762,0.00004749139,0.005791946,0.00000467401,0.000004749725,0.00002116186,0.00002219755,0.9891188,0.004731917,0.00006831889,0.0001566204,0.0000105572],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9728261,0.00008309443,0.01925973,0.0000849095,0.00001737444,0.00005511957,0.001089457,0.001117298,0.00546694],"genre_scores_gemma":[0.9961373,0.00003527652,0.002927913,0.000007491447,0.000002338106,0.00001775531,0.0004388579,0.00002610233,0.0004069236],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01240734,"threshold_uncertainty_score":0.02467024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01924048571929628,"score_gpt":0.2276937356328551,"score_spread":0.2084532499135588,"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."}}