{"id":"W3200195263","doi":"10.1109/tmech.2021.3105950","title":"Comparison of Decentralized ADMM Optimization Algorithms for Power Allocation in Modular Fuel Cell Vehicles","year":2021,"lang":"en","type":"article","venue":"IEEE/ASME Transactions on Mechatronics","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydrogenics (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Modular design; Powertrain; Modularity (biology); Computer science; Flexibility (engineering); Robustness (evolution); Distributed computing; Mathematical optimization; Mathematics; Torque","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001169203,0.000179902,0.0002920764,0.0002407351,0.00005345984,0.00001997172,0.0001945823,0.0002097159,0.00007528878],"category_scores_gemma":[0.00001951833,0.000214447,0.0001019586,0.0005003097,0.00003398291,0.0001876314,0.000003636332,0.0003404979,0.000006435295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003016766,"about_ca_system_score_gemma":0.00007643244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003539726,"about_ca_topic_score_gemma":0.00004840553,"domain_scores_codex":[0.9986652,0.00003695119,0.000409529,0.0002667885,0.0002438292,0.0003777433],"domain_scores_gemma":[0.9992449,0.0001301376,0.00005138016,0.0003779674,0.0001459303,0.00004963261],"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":[0.00003205214,0.0002326428,0.00001328543,0.0001737271,0.00002788215,0.000001255428,0.0001282356,0.9512058,0.04117805,0.00009615679,0.00002337656,0.006887547],"study_design_scores_gemma":[0.000708281,0.00007726151,0.000007470978,0.00002856749,0.00001283618,8.36068e-7,0.0003339311,0.6074675,0.3905539,0.0002599595,0.0004211468,0.0001283237],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0341213,0.00101537,0.9636546,0.0001476872,0.0002781332,0.0004196661,0.00006562014,0.0002421027,0.00005550509],"genre_scores_gemma":[0.8724226,0.001349,0.1259517,0.00001025721,0.000005849302,0.0001223253,0.00004210969,0.00005087016,0.00004521225],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8383014,"threshold_uncertainty_score":0.8744894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02717107101014318,"score_gpt":0.3070880006254658,"score_spread":0.2799169296153226,"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."}}