{"id":"W2040084934","doi":"10.1504/ijmme.2014.066577","title":"A multi-step approach to long-term open-pit production planning","year":2014,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Natural Resources; University of Alberta","funders":"","keywords":"Integer programming; Scheduling (production processes); Mathematical optimization; Heuristic; Cluster analysis; Production planning; Computer science; Open-pit mining; Linear programming; Key (lock); Term (time); Hierarchical clustering; Production (economics); Engineering; Algorithm; Mathematics; Machine learning","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":[0.001841591,0.0008458984,0.0007829398,0.0007319894,0.0005567937,0.001218372,0.002219147,0.0009619975,0.005740236],"category_scores_gemma":[0.002181738,0.0008846144,0.001214233,0.0008291794,0.000702709,0.001060209,0.001451795,0.001402335,0.0005553846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001229386,"about_ca_system_score_gemma":0.002375413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003902976,"about_ca_topic_score_gemma":0.006753339,"domain_scores_codex":[0.9991459,0.0003206145,0.00004298895,0.0001440522,0.0002591233,0.00008722103],"domain_scores_gemma":[0.9988534,0.000675584,0.0001373903,0.000086154,0.0001929314,0.000054502],"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":[0.00001924921,0.00003004851,0.0001633316,0.00009076251,0.00002001645,0.00005324932,0.00005308732,0.9743177,0.001294265,0.007803275,0.0001841212,0.01597097],"study_design_scores_gemma":[0.000008555729,0.00008784014,0.0001058075,0.00001751283,0.00001021898,0.00002150529,0.00002745811,0.9910223,0.001001869,0.006067083,0.001620006,0.000009718406],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004383293,0.00006668039,0.9928797,0.00005240687,0.00001046603,0.000106934,0.00003857244,0.00006944801,0.002392512],"genre_scores_gemma":[0.23825,0.0001939487,0.7568088,0.0000516422,0.00001674096,0.0005811555,0.0001425948,0.00007766444,0.003877449],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005740236,"threshold_uncertainty_score":0.01920295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02718972613945285,"score_gpt":0.2628570186568205,"score_spread":0.2356672925173676,"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."}}