{"id":"W4411855369","doi":"10.20944/preprints202507.0089.v1","title":"Bayesian Predictive Model for Electric Level 4 Connected Automated Vehicle Adoption","year":2025,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bayesian probability; Computer science; Electric vehicle; Econometrics; Artificial intelligence; Mathematics; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003835623,0.0009355004,0.001344452,0.001243235,0.000431885,0.001901118,0.002062513,0.001898178,0.005239523],"category_scores_gemma":[0.01091163,0.0008033534,0.001095154,0.001293762,0.001185572,0.001915534,0.001024933,0.001976083,0.0007654043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002486428,"about_ca_system_score_gemma":0.001318864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0480526,"about_ca_topic_score_gemma":0.02530432,"domain_scores_codex":[0.9987877,0.000484349,0.00004572739,0.0002704069,0.000218212,0.0001935947],"domain_scores_gemma":[0.9936226,0.004845453,0.0006876775,0.000155321,0.0005698887,0.000119111],"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":[0.00008980129,0.00003982056,0.003137437,0.00003212624,0.00003599286,0.00008311284,0.00008066413,0.965288,0.0002297213,0.02343776,0.000862018,0.006683472],"study_design_scores_gemma":[0.000009121401,0.00001647123,0.0008783258,0.00001114912,0.00001391553,0.00001175372,0.0000201522,0.991272,0.00005602353,0.007349438,0.0003483958,0.00001314831],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2987449,0.001028689,0.6770205,0.002455576,0.00009266259,0.0002334583,0.002668456,0.000568691,0.01718712],"genre_scores_gemma":[0.9672737,0.0007283174,0.01955706,0.000163506,0.00005016728,0.0002562371,0.001423548,0.00004852938,0.01049903],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0480526,"threshold_uncertainty_score":0.09554583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0525254867883892,"score_gpt":0.2923163389927254,"score_spread":0.2397908522043362,"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."}}