{"id":"W7161754061","doi":"10.82308/41719","title":"LOGISTICAL CONTROL OF IRON ORE STREAMS UNDER GEOLOGICAL AND MARKET UNCERTAINTY","year":2024,"lang":"en","type":"dissertation","venue":"","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Iron ore; Leverage (statistics); Productivity; Control (management); Sustainability; Mill; Mining industry; Quality (philosophy); Commodity; Automation","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":[0.00151662,0.0009125886,0.0008685556,0.0006401107,0.0007825072,0.002748265,0.001183031,0.001345853,0.002680433],"category_scores_gemma":[0.004692171,0.0006734742,0.0007839212,0.000519343,0.00125085,0.001653354,0.002268215,0.001340572,0.0002668992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002088604,"about_ca_system_score_gemma":0.002808771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03142652,"about_ca_topic_score_gemma":0.01545403,"domain_scores_codex":[0.9990569,0.0002181964,0.00004253654,0.0001965803,0.0002211196,0.0002647183],"domain_scores_gemma":[0.9981166,0.001005503,0.0003764037,0.00007555648,0.0002823503,0.0001436465],"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":[0.0001550002,0.00002801785,0.001997995,0.0000430091,0.00002768568,0.0001822214,0.00007507583,0.9789196,0.001546039,0.01172035,0.0003538833,0.004951145],"study_design_scores_gemma":[0.00001272364,0.0000340429,0.0004033771,0.000005826952,0.000008073575,0.00001781759,0.00005284588,0.9940633,0.0003233463,0.004621668,0.0004467601,0.00001012207],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4250422,0.0008244929,0.5434904,0.001966101,0.0001128209,0.000212337,0.0007101086,0.0006505676,0.02699093],"genre_scores_gemma":[0.9912707,0.0001617718,0.006258477,0.00004257546,0.000009583129,0.00003734206,0.00009216529,0.00002009341,0.002107382],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03142652,"threshold_uncertainty_score":0.06248719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01044619212191764,"score_gpt":0.2329740898031794,"score_spread":0.2225278976812617,"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."}}