{"id":"W4403603330","doi":"10.3390/ijgi13100368","title":"Discovering Electric Vehicle Charging Locations Based on Clustering Techniques Applied to Vehicular Mobility Datasets","year":2024,"lang":"en","type":"article","venue":"ISPRS International Journal of Geo-Information","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of the Fraser Valley","funders":"","keywords":"Cluster analysis; Electric vehicle; Computer science; Data mining; Artificial intelligence; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.0003916367,0.0001384323,0.0001276855,0.0008893528,0.00006372173,0.0002708288,0.0002799668,0.000057855,0.0000465606],"category_scores_gemma":[0.00005441406,0.0001378573,0.00007902716,0.0004335828,0.00001173901,0.001723499,0.00001506829,0.000275394,0.0000669083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003553446,"about_ca_system_score_gemma":0.00008098175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001242077,"about_ca_topic_score_gemma":0.000008880647,"domain_scores_codex":[0.9985648,0.000009396804,0.0006913897,0.00008283147,0.000501667,0.0001499405],"domain_scores_gemma":[0.9993532,0.00006076774,0.00009641533,0.0001591779,0.0002573859,0.00007310167],"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":[0.0000739797,0.00005333944,0.0001029021,0.0001349434,0.0001162827,0.000007011534,0.00084494,0.9060837,0.01279749,0.00418235,0.001921709,0.07368135],"study_design_scores_gemma":[0.0005037034,0.00009930845,0.007682631,0.000431949,0.00004412511,0.00002629474,0.0002571768,0.8576242,0.0376962,0.0002141974,0.09508481,0.0003354065],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09963057,0.00002796961,0.8950573,0.001270006,0.001272023,0.0003610851,0.0003173958,0.0003282294,0.001735446],"genre_scores_gemma":[0.9963551,0.00001851495,0.002465551,0.0005726042,0.0001330244,0.00003794128,0.0004014029,0.00001275069,0.00000307783],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8967246,"threshold_uncertainty_score":0.5621657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005349292472257604,"score_gpt":0.2457270568639461,"score_spread":0.2403777643916885,"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."}}