{"id":"W4319297857","doi":"10.3390/electronics12040790","title":"Applications of Clustering Methods for Different Aspects of Electric Vehicles","year":2023,"lang":"en","type":"article","venue":"Electronics","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Canada First Research Excellence Fund","keywords":"Cluster analysis; Computer science; Data mining; Operations research; Engineering; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0001524599,0.0001222358,0.0002421164,0.0001811736,0.00003630632,0.000006108139,0.0001737365,0.00008250265,0.000006726121],"category_scores_gemma":[0.00001958041,0.0001169931,0.00009427743,0.000806449,0.0000116714,0.00003290383,0.0000209077,0.0001512572,0.000001548605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007374907,"about_ca_system_score_gemma":0.00003603519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001086505,"about_ca_topic_score_gemma":0.000009493344,"domain_scores_codex":[0.999147,0.00001758147,0.0002653016,0.0001245898,0.00008615561,0.0003593936],"domain_scores_gemma":[0.9994909,0.0001621814,0.00006075005,0.000197132,0.00005426212,0.00003483329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000008374573,0.00001333514,0.00004014884,0.0002484547,0.00007819649,7.878468e-8,0.00006406437,0.006763002,0.5816564,0.01027449,0.0003403354,0.4005131],"study_design_scores_gemma":[0.0002518462,0.0001737764,0.0006865302,0.00001134636,0.00003542903,0.000002522141,0.00001211751,0.2492751,0.7096956,0.02214513,0.01757102,0.0001395866],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1848517,0.0124516,0.8000858,0.0000537037,0.00008597597,0.0007152531,0.00001465904,0.0004098682,0.001331441],"genre_scores_gemma":[0.9919099,0.001547625,0.006233325,0.000007707394,0.00006514397,0.0001211322,0.00001840142,0.00004459962,0.000052123],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8070583,"threshold_uncertainty_score":0.4770842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008742816815614287,"score_gpt":0.2726506453840842,"score_spread":0.2639078285684699,"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."}}