{"id":"W4413805226","doi":"10.1016/j.rineng.2025.106995","title":"Analyzing internet of things emergence for modern electric vehicle industry","year":2025,"lang":"en","type":"article","venue":"Results in Engineering","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"University of Tabriz","keywords":"Internet of Things; Electric vehicle; Industrial Internet; The Internet; Business; Computer security; Computer science; Internet privacy; Engineering; Commerce; World Wide Web; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000613232,0.0003639469,0.000184838,0.002052256,0.000678461,0.002306326,0.0003376052,0.000922606,0.002869049],"category_scores_gemma":[0.002265594,0.0001524247,0.0004848373,0.002365704,0.0005270088,0.003620094,0.001107199,0.0009994688,0.0007779336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001025633,"about_ca_system_score_gemma":0.0005309289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00270168,"about_ca_topic_score_gemma":0.003941865,"domain_scores_codex":[0.9994957,0.00007886433,0.00002774223,0.0001042047,0.0001906695,0.0001027519],"domain_scores_gemma":[0.9992004,0.0002668448,0.0001408206,0.00007104315,0.0002594735,0.00006150056],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002361029,0.0002510707,0.2329068,0.0008530243,0.0001732854,0.004449174,0.003461813,0.03254554,0.007992369,0.3903187,0.06617864,0.2606335],"study_design_scores_gemma":[0.00001662601,0.0001515062,0.2227356,0.0008838694,0.0001386855,0.002395351,0.01293962,0.1711901,0.004052247,0.1479677,0.4373692,0.0001595458],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6031909,0.01521035,0.07300611,0.02125132,0.001552601,0.0002757974,0.005932151,0.0006083688,0.2789724],"genre_scores_gemma":[0.9778566,0.004882347,0.00663375,0.0008851134,0.0003136658,0.00006726049,0.001913733,0.00006832764,0.007379157],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002869049,"threshold_uncertainty_score":0.009597898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005067745524620614,"score_gpt":0.2132145018090144,"score_spread":0.2081467562843938,"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."}}