{"id":"W4293221244","doi":"10.3390/mining2030028","title":"Optimum Fleet Selection Using Machine Learning Algorithms—Case Study: Zenouz Kaolin Mine","year":2022,"lang":"en","type":"article","venue":"Mining","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Loader; Truck; Excavator; Decision tree; Boosting (machine learning); Gradient boosting; Computer science; Algorithm; Selection (genetic algorithm); Engineering; Random forest; Machine learning; Automotive engineering","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":[0.00131843,0.000707672,0.0006862041,0.001164691,0.0008312272,0.0007954972,0.001005653,0.001362678,0.00121677],"category_scores_gemma":[0.00213169,0.0003257621,0.0006636233,0.00150042,0.000481076,0.0009098063,0.0005097774,0.00044712,0.0001779332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001431709,"about_ca_system_score_gemma":0.001091781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02258925,"about_ca_topic_score_gemma":0.0242878,"domain_scores_codex":[0.999459,0.0002185179,0.00002903004,0.00009207745,0.00009494957,0.0001063545],"domain_scores_gemma":[0.9989421,0.0006816227,0.00008795946,0.00006904874,0.0001425794,0.0000767398],"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":[0.0002111508,0.0002355757,0.01189315,0.00009175869,0.00004767679,0.001474337,0.00009056746,0.9601028,0.001066544,0.001468229,0.0007802345,0.02253804],"study_design_scores_gemma":[0.00003843232,0.0001607586,0.004743434,0.000009229625,0.0000202437,0.0001789492,0.0001957591,0.9914932,0.001528,0.0008186662,0.0007964132,0.00001679746],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.956118,0.0002290396,0.03932108,0.0003122583,0.00001774469,0.000121561,0.0003118422,0.0001431975,0.003425317],"genre_scores_gemma":[0.9785029,0.0000877319,0.01975818,0.00001689382,0.000005755193,0.00005354588,0.0002289887,0.00001484319,0.001331121],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02258925,"threshold_uncertainty_score":0.0449155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02982554798695608,"score_gpt":0.2513712618881466,"score_spread":0.2215457139011905,"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."}}