{"id":"W3114396658","doi":"10.11606/d.55.2020.tde-23112020-143732","title":"Problema de Roteamento de Veículos Elétricos: otimização da vida útil das baterias","year":2020,"lang":"pt","type":"dissertation","venue":"","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Discovery Air (Canada)","funders":"","keywords":"Memetic algorithm; Greenhouse gas; Problem solver; Solver; Computer science; Energy consumption; Mathematical optimization; Operations research; Engineering; Evolutionary algorithm; Mathematics; Artificial intelligence; Electrical 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002182882,0.001005547,0.0008773598,0.0002817549,0.000209007,0.0004730736,0.0007149759,0.001101754,0.003379162],"category_scores_gemma":[0.00009445055,0.001021557,0.0003464289,0.0008705449,0.00002055553,0.000273912,0.00007987989,0.001304731,0.0002257939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008226792,"about_ca_system_score_gemma":0.0004406383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004457526,"about_ca_topic_score_gemma":0.00005552369,"domain_scores_codex":[0.9963083,0.0001166074,0.0009194752,0.000821625,0.0004995099,0.001334474],"domain_scores_gemma":[0.9984447,0.00006648134,0.0002600931,0.0005211807,0.0001372745,0.0005702358],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008206622,0.0005054216,0.003271829,0.01532537,0.003682357,0.0005820168,0.03557279,0.2333163,0.4695845,0.007788147,0.08090518,0.1486454],"study_design_scores_gemma":[0.002662127,0.001074197,0.005321991,0.001066418,0.001004614,0.0001489976,0.00350845,0.7777323,0.1719054,0.001844292,0.03012672,0.003604417],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6936419,0.006100893,0.2206185,0.004040316,0.004121911,0.006393815,0.0003355352,0.003501934,0.06124518],"genre_scores_gemma":[0.9697896,0.0007634918,0.01576291,0.0009853698,0.0006260842,0.0002291524,0.001685007,0.0004514054,0.009706961],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5444161,"threshold_uncertainty_score":0.9992235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008485772969751495,"score_gpt":0.242367064236905,"score_spread":0.2338812912671535,"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."}}