{"id":"W2982158442","doi":"","title":"DYNAMIC MODELLING OF A SAG MILL-PEBBLE CRUSHER CIRCUIT BY DATA-DRIVEN METHODS","year":2019,"lang":"en","type":"article","venue":"Chalmers Research (Chalmers University of Technology)","topic":"Mineral Processing and Grinding","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Crusher; Comminution; Mill; Artificial neural network; Computer science; Power (physics); Process (computing); Engineering; Artificial intelligence; Mechanical engineering; Materials science; Metallurgy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003226662,0.0005330322,0.0005304016,0.0003915459,0.0002593226,0.0007850814,0.0006821186,0.0008598116,0.001069751],"category_scores_gemma":[0.0006594531,0.0004055162,0.0006241903,0.0003851479,0.0002438889,0.0004356472,0.000326892,0.0007168401,0.0001711661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006344546,"about_ca_system_score_gemma":0.0006966604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03237444,"about_ca_topic_score_gemma":0.02506249,"domain_scores_codex":[0.9998937,0.00001779513,0.000007352078,0.00003587296,0.00002779155,0.00001754401],"domain_scores_gemma":[0.9997756,0.0001143813,0.00002856139,0.000009923711,0.00005993926,0.0000115391],"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":[0.00001725812,0.00001260283,0.0006447437,0.00001960153,0.00001331832,0.0000344316,0.00001684406,0.9927463,0.001170898,0.0003304061,0.0001103188,0.004883293],"study_design_scores_gemma":[6.176223e-7,0.000002770149,0.0001361691,8.370236e-7,0.000001125988,0.000001759634,0.00000204744,0.999559,0.0001296487,0.00008603129,0.00007882187,0.00000123696],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3046853,0.0005554401,0.6862792,0.000383159,0.00008454331,0.00009345633,0.0009940721,0.001154088,0.005770733],"genre_scores_gemma":[0.9809441,0.0001397565,0.01614512,0.00002527585,0.000009614108,0.00007681855,0.0004097617,0.00002980461,0.00221987],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03237444,"threshold_uncertainty_score":0.064372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09724304813700713,"score_gpt":0.3301113917651234,"score_spread":0.2328683436281163,"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."}}