{"id":"W4414694237","doi":"10.1016/j.segan.2025.101994","title":"A multi-faceted strategy for scalable, efficient, and grid-integrated electric vehicle systems using solid-state batteries and AI technologies","year":2025,"lang":"en","type":"article","venue":"Sustainable Energy Grids and Networks","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Battery (electricity); Scalability; Electric vehicle; Smart grid; Modular design; Renewable energy; Grid; Tariff; Energy management","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":[0.0001945867,0.0004554542,0.0004547269,0.0003965009,0.0006649677,0.001212032,0.0008858767,0.0004395116,0.004460522],"category_scores_gemma":[0.0002984904,0.0001645334,0.0003272222,0.0004951599,0.0003305341,0.001212028,0.00174051,0.000536719,0.001356172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004915838,"about_ca_system_score_gemma":0.0008782307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001693762,"about_ca_topic_score_gemma":0.003746531,"domain_scores_codex":[0.9998239,0.0000179049,0.000009161184,0.00003484511,0.00006712422,0.0000471659],"domain_scores_gemma":[0.9998373,0.00001963969,0.00001437405,0.00003068842,0.00007184791,0.00002609958],"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":[0.0002924233,0.0003528173,0.00237821,0.0003464707,0.0001151881,0.0006742218,0.0002867465,0.1896991,0.418827,0.08724514,0.007959411,0.2918234],"study_design_scores_gemma":[0.00001791315,0.0002735936,0.0007569381,0.00003073604,0.00003786916,0.0002356799,0.0003469443,0.8730245,0.07259338,0.03228427,0.02035943,0.00003878221],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1071378,0.0007256816,0.8330272,0.000609188,0.0001727412,0.0002157611,0.0002206979,0.001414682,0.05647628],"genre_scores_gemma":[0.8694431,0.000344495,0.1182689,0.000134967,0.00002636429,0.0001201087,0.0002201872,0.00006104229,0.01138082],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004460522,"threshold_uncertainty_score":0.0149219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008920379245348942,"score_gpt":0.2596851128205721,"score_spread":0.2507647335752231,"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."}}