{"id":"W4405323921","doi":"10.1177/25726668241301876","title":"An intelligent rule-based decision-making system for preliminary truck dispatching within open-pit mines","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":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Truck; Adaptability; Shovel; Computer science; Process (computing); Engineering; Artificial neural network; Reduction (mathematics); Range (aeronautics); Real-time computing; Operations research; Artificial intelligence; 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":[0.001077464,0.000603849,0.0007600699,0.0004502907,0.0005983966,0.001063308,0.001550885,0.00097948,0.002387487],"category_scores_gemma":[0.002401706,0.0003722984,0.0004357259,0.0003462312,0.0003663721,0.0008416445,0.0006266626,0.0008701121,0.000712741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007070842,"about_ca_system_score_gemma":0.001518431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006320608,"about_ca_topic_score_gemma":0.00538704,"domain_scores_codex":[0.9995775,0.00006267286,0.00004940806,0.0001614057,0.00009653631,0.00005253075],"domain_scores_gemma":[0.9990304,0.0003449128,0.0001185874,0.00007862234,0.0003403221,0.00008708412],"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":[0.0004901067,0.0005821707,0.003625397,0.0001264778,0.00007722298,0.0005252878,0.0002370505,0.7385554,0.01868835,0.003102173,0.003205965,0.2307844],"study_design_scores_gemma":[0.00002089142,0.00006318923,0.0002549522,0.000005872953,0.00001234209,0.00001892873,0.00001038579,0.9964156,0.002002101,0.0006895507,0.0004969945,0.000009073655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08499223,0.0001508168,0.9052598,0.0003238,0.0001455099,0.0002912221,0.0002095059,0.004640969,0.003986222],"genre_scores_gemma":[0.8512765,0.00008319182,0.1457214,0.000141172,0.00003284336,0.0002257802,0.0002318604,0.00004205504,0.002245208],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006320608,"threshold_uncertainty_score":0.01256764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0229505359706728,"score_gpt":0.279668903183115,"score_spread":0.2567183672124422,"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."}}