{"id":"W3189623251","doi":"10.3390/mining1020012","title":"Mathematical Programming Application in Sublevel Caving Production Scheduling","year":2021,"lang":"en","type":"article","venue":"Mining","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Scheduling (production processes); Profitability index; Rock blasting; Production schedule; Schedule; Operations research; Engineering; Flexibility (engineering); Production (economics); Computer science; Mining engineering; Industrial engineering; Operations management; Mathematics; Business; Economics","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":[0.0002427632,0.00008166549,0.000119032,0.00005984028,0.00003407602,0.00003926145,0.00005531024,0.00006156493,0.00001261559],"category_scores_gemma":[0.00006957178,0.0001009976,0.0000217775,0.0001596794,0.000008270245,0.0001070769,0.0000275154,0.000117294,0.00001479912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000830637,"about_ca_system_score_gemma":0.00001355665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003654665,"about_ca_topic_score_gemma":0.00002739632,"domain_scores_codex":[0.9993649,0.000006945545,0.0002214098,0.0001711395,0.00004583624,0.0001898323],"domain_scores_gemma":[0.9997461,0.00002051351,0.00002239769,0.0001648255,0.0000178978,0.0000281957],"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":[0.000007249841,0.0001244173,0.02499708,0.0008538405,0.00004507951,0.00004443282,0.007592764,0.1288615,0.04895829,0.006481207,0.0002280396,0.7818061],"study_design_scores_gemma":[0.0002225566,0.00001392232,0.00152218,0.0004288509,0.00001467943,0.00007212199,0.002186862,0.9394798,0.04894084,0.001437369,0.005213484,0.0004673492],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8944283,0.0001448402,0.1032378,0.00005748415,0.00009613251,0.0001029206,3.157076e-7,0.0003329381,0.001599356],"genre_scores_gemma":[0.7555642,0.00001560787,0.2442156,0.000006690166,0.00007401905,0.00006051675,0.000006740235,0.00002217225,0.00003454193],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8106183,"threshold_uncertainty_score":0.4118562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01997976173503895,"score_gpt":0.2341991058397607,"score_spread":0.2142193441047217,"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."}}