{"id":"W4213285145","doi":"10.1007/978-3-030-91589-6_20","title":"Advanced Analytics for Energy-Efficiency Improvement in Mine-Railway Operation","year":2022,"lang":"en","type":"book-chapter","venue":"","topic":"Railway Systems and Energy Efficiency","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Engineering; Automotive engineering; Energy consumption; Fuel efficiency; Diesel fuel; Artificial neural network; Computer science; Artificial intelligence","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":[0.0004671119,0.001230151,0.0007839387,0.00136382,0.000263462,0.003263814,0.0008376485,0.00070758,0.01614667],"category_scores_gemma":[0.001305671,0.00034753,0.0005055459,0.002635433,0.0005806595,0.004149718,0.000942115,0.001432189,0.008578491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007188353,"about_ca_system_score_gemma":0.0005175274,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001295936,"about_ca_topic_score_gemma":0.001746569,"domain_scores_codex":[0.9994061,0.00006333846,0.00002165047,0.00007210419,0.0004090912,0.000027635],"domain_scores_gemma":[0.9995409,0.0002455499,0.00002435448,0.0000488349,0.0001303576,0.00001002194],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004355427,0.00008810833,0.0005336839,0.0005139826,0.00003111763,0.00008273098,0.0001504021,0.02014509,0.003998631,0.2067533,0.106269,0.6613904],"study_design_scores_gemma":[0.000007042334,0.00006246827,0.002007687,0.0004282355,0.00003096243,0.0003050401,0.0002580888,0.1099631,0.009796038,0.3817732,0.4953184,0.00004959848],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005490596,0.03450888,0.7119288,0.002931194,0.001642567,0.0001057998,0.0012648,0.004221865,0.2379055],"genre_scores_gemma":[0.1597591,0.05538726,0.30471,0.001088552,0.001913068,0.000180467,0.003318725,0.001919518,0.4717233],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01614667,"threshold_uncertainty_score":0.05401593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01075336452608309,"score_gpt":0.2057296894499737,"score_spread":0.1949763249238906,"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."}}