{"id":"W2057048716","doi":"10.4028/www.scientific.net/amr.429.206","title":"Mining Plan Optimization Based on Linear Programming in Shirengou Iron Mine","year":2012,"lang":"en","type":"article","venue":"Advanced materials research","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Iron Ore Company (Canada)","funders":"","keywords":"Plan (archaeology); Linear programming; Process (computing); Control (management); Quality (philosophy); Joint (building); Engineering; Mathematical optimization; Mining engineering; Computer science; Civil engineering; Mathematics; Geology; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007938194,0.0005359029,0.0009727922,0.000476961,0.0003484926,0.001083602,0.0004920228,0.0007256762,0.001441874],"category_scores_gemma":[0.001046674,0.0005542067,0.0006032294,0.0005395681,0.0006223224,0.0006355531,0.0005507912,0.0006921956,0.00009526408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001202691,"about_ca_system_score_gemma":0.001354537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01767485,"about_ca_topic_score_gemma":0.0126735,"domain_scores_codex":[0.9997323,0.0001186771,0.000009407987,0.00004590466,0.00004410349,0.0000495349],"domain_scores_gemma":[0.9995641,0.0003120411,0.00004805882,0.000007154493,0.0000500576,0.00001859102],"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":[0.00001359693,0.00001413812,0.0001550651,0.00001613004,0.000005969825,0.00002853179,0.00001321278,0.9952235,0.0001720783,0.0022362,0.00007884751,0.002042881],"study_design_scores_gemma":[0.000002895314,0.00001168286,0.00004658912,0.000001538909,0.000002112803,0.000002507911,0.000008753553,0.9988587,0.00004891941,0.0009560119,0.00005865035,0.000001645072],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2433859,0.0006473653,0.7409924,0.0007928453,0.00003528291,0.0001053875,0.0001504476,0.0001554476,0.01373495],"genre_scores_gemma":[0.9394236,0.0003311818,0.05574,0.00006204556,0.00001145567,0.0001668683,0.00007246028,0.00002988072,0.004162584],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01767485,"threshold_uncertainty_score":0.03514391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06032122668864088,"score_gpt":0.3346420457694498,"score_spread":0.2743208190808089,"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."}}