{"id":"W4401033185","doi":"10.1177/25726668241263408","title":"Simultaneous stochastic optimisation of mining complexes with equipment uncertainty: Application at an open-pit copper mining complex","year":2024,"lang":"en","type":"article","venue":"Mining Technology Transactions of the Institutions of Mining and Metallurgy","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Copper mine; Open-pit mining; Copper; Copper mining; Mining engineering; Data mining; Computer science; Engineering; Metallurgy; Materials science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000308796,0.0002718765,0.0005260982,0.0005116599,0.0003123749,0.00003551536,0.0006231255,0.0002143202,0.00004125028],"category_scores_gemma":[0.00004965467,0.0002390262,0.00008064578,0.0005533959,0.0007766262,0.0002249196,0.0001086034,0.0001653383,9.105872e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001427184,"about_ca_system_score_gemma":0.0001378541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009018784,"about_ca_topic_score_gemma":0.0004100973,"domain_scores_codex":[0.9985079,0.00002830018,0.0006773007,0.0003696097,0.0001471838,0.0002697152],"domain_scores_gemma":[0.9987643,0.0002649194,0.0002027037,0.0006097588,0.00009746663,0.00006087794],"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":[0.00006567412,0.0001014302,0.00009665985,0.000219241,0.0003447492,0.000002546577,0.002617173,0.9358643,0.03129328,0.003025009,0.00007100227,0.02629893],"study_design_scores_gemma":[0.0007528258,0.0007309111,0.00007817265,0.001068802,0.000547359,0.0002201783,0.00714395,0.9702578,0.01588897,0.0001482254,0.002690158,0.0004726058],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.780804,0.0003047719,0.2173788,0.0001480906,0.0001308309,0.0003369125,0.00006733347,0.000304866,0.0005244036],"genre_scores_gemma":[0.8819874,0.00004823565,0.117683,0.000008149961,0.00001087817,0.0001109147,0.00002649584,0.0000380503,0.00008688867],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1011834,"threshold_uncertainty_score":0.9747204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03271246534937313,"score_gpt":0.2675548156573728,"score_spread":0.2348423503079997,"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."}}