{"id":"W4403906138","doi":"10.56294/dm2025466","title":"Blockchain-Powered Energy Optimization in Metro Networks: A Case Study on Electric Braking","year":2024,"lang":"en","type":"article","venue":"Data & Metadata","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Automotive engineering; Dynamic braking; Blockchain; Energy (signal processing); Computer science; Engineering; Computer security; Retarder; 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":[0.001028402,0.0002099549,0.0002542251,0.0006457776,0.0001557984,0.0005040697,0.002986352,0.000117912,0.00000931563],"category_scores_gemma":[0.00009060046,0.0001963664,0.00002895363,0.003250309,0.00002457971,0.0007253365,0.001676937,0.0003842951,0.000006782962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006004814,"about_ca_system_score_gemma":0.00007233264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000825379,"about_ca_topic_score_gemma":0.001239966,"domain_scores_codex":[0.9976262,0.0001817271,0.000381554,0.001206336,0.0002432696,0.0003608877],"domain_scores_gemma":[0.9956726,0.0002510702,0.00007419416,0.003909337,0.00003205102,0.00006076613],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002740022,0.002724742,0.0007094538,0.00003718061,0.0005557711,0.01373148,0.0008408342,0.04184499,0.00007554359,0.4766292,0.01125268,0.4515707],"study_design_scores_gemma":[0.0002152512,0.00009372566,0.00002544701,0.0000149449,0.0000349552,0.0002476404,0.0001640368,0.9915186,0.00003942139,0.0006430132,0.006805199,0.000197808],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0132595,0.002451302,0.9826002,0.0005128169,0.0002153535,0.0003332783,0.00009382304,0.0004714788,0.00006226954],"genre_scores_gemma":[0.9807644,0.00007976029,0.0184468,0.0002095691,0.00006426578,0.00008398186,0.0003058629,0.00001911768,0.00002621333],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9675049,"threshold_uncertainty_score":0.8007588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03408013179870122,"score_gpt":0.2948151576914948,"score_spread":0.2607350258927936,"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."}}