{"id":"W4403895764","doi":"10.18280/mmep.111004","title":"Machine Learning Techniques for Predicting the Quantity of ANFO Used in Blasting a Bench in an Open Pit Mine","year":2024,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Mineral Processing and Grinding","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Rock blasting; Open-pit mining; Mining engineering; Engineering; Environmental science; Petroleum engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001029083,0.0001766202,0.0002982364,0.0001824282,0.00004874681,0.0001835223,0.0001911812,0.00008601251,0.000002512901],"category_scores_gemma":[0.00007847888,0.0001380455,0.0000279926,0.0002815599,0.00001890718,0.0002513828,0.00005996551,0.0003926776,6.941976e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002950196,"about_ca_system_score_gemma":0.000008981414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007404981,"about_ca_topic_score_gemma":0.00002865949,"domain_scores_codex":[0.9989399,0.00001433325,0.0004495867,0.0002109875,0.0001028401,0.0002824017],"domain_scores_gemma":[0.9994699,0.0003318109,0.00002576733,0.0001099353,0.00001658913,0.00004593251],"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":[0.000003263237,0.00002084182,0.0006467343,0.003336103,0.00001018147,0.000001633872,0.002405626,0.9869633,0.003909619,0.001702697,0.000001185705,0.0009988069],"study_design_scores_gemma":[0.0001323038,0.00006523919,0.00001615842,0.002355918,0.00001161567,0.000006502429,0.00007289457,0.9930481,0.000726042,0.00334753,0.00005883131,0.0001588494],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5557427,0.0007589744,0.4427155,0.00002703058,0.00003536202,0.0003316129,0.000004485476,0.0002700575,0.0001142386],"genre_scores_gemma":[0.9651168,0.00004445859,0.03461403,0.000001601629,0.00003529635,0.0001096134,0.000005970344,0.00005242603,0.00001979338],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4093741,"threshold_uncertainty_score":0.5629332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04346697318710237,"score_gpt":0.2655620995255032,"score_spread":0.2220951263384009,"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."}}