{"id":"W2140073517","doi":"10.1109/acc.2009.5160724","title":"Data mining based feedback regulation in operation of hematite ore mineral processing plant","year":2009,"lang":"en","type":"article","venue":"","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Compensation (psychology); Set (abstract data type); Production (economics); Association rule learning; Data mining; Rough set; Mineral processing; State (computer science); Control theory (sociology); Feedback loop; Artificial intelligence; Control (management); Algorithm","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002450862,0.00006318341,0.0001009355,0.00007451419,0.00003275153,0.00009105045,0.000431241,0.00003125193,0.000009571728],"category_scores_gemma":[0.00001885259,0.00004828429,0.000009017866,0.0002373701,0.000008936245,0.0008076591,0.00005757736,0.00003180754,0.000001877597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001190093,"about_ca_system_score_gemma":0.00004893887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001515962,"about_ca_topic_score_gemma":0.00005708297,"domain_scores_codex":[0.9992718,0.00002266137,0.0002238817,0.0002255318,0.0001513781,0.0001047958],"domain_scores_gemma":[0.9994821,0.0000181318,0.00006967319,0.0003824316,0.00002734547,0.00002030179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007493648,0.0006944987,0.009454281,0.0002499096,0.000008867579,0.00002965943,0.004576993,0.06092078,0.03054768,0.0311171,0.01242252,0.8499027],"study_design_scores_gemma":[0.0002311516,0.00004393035,0.03315512,0.00005952471,0.000001013773,0.000002502066,0.00002026946,0.9654331,0.0006067622,0.0003118548,0.00006795322,0.00006678878],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09594322,0.00007298319,0.8938239,0.002536079,0.00006453258,0.0002038634,0.000009450161,0.00007684341,0.007269196],"genre_scores_gemma":[0.7180994,6.629247e-7,0.2815455,0.0002396231,0.00001684382,6.523006e-7,0.0000702234,0.000001335456,0.00002585428],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9045123,"threshold_uncertainty_score":0.1968976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05580834962348621,"score_gpt":0.2752519003592121,"score_spread":0.2194435507357259,"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."}}