{"id":"W2626864102","doi":"","title":"Parallelized FMM and Dedicated PEEC Method to Model Industrial Power Interconnections - Application to Boost Chopper","year":2011,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Copper Interconnects and Reliability","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Center for Diagnosis and Research on Alzheimer's Disease","funders":"","keywords":"Chopper; Computer science; Power (physics); Electronic engineering; Electrical engineering; Engineering; Voltage; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.007114376,0.0004603789,0.0006001929,0.0003086339,0.0004003841,0.000466068,0.001369915,0.0004555839,0.0006498831],"category_scores_gemma":[0.002138324,0.0004385601,0.0001889344,0.0003657131,0.0001974122,0.000161924,0.002736414,0.0007312683,0.0002124973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002244772,"about_ca_system_score_gemma":0.0003398165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004982189,"about_ca_topic_score_gemma":0.002509599,"domain_scores_codex":[0.9935542,0.003209496,0.0008076816,0.001523425,0.0004125195,0.0004926923],"domain_scores_gemma":[0.9941336,0.0008067273,0.000366063,0.00237277,0.001748719,0.0005721555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005968369,0.00249594,0.00126131,0.0002950861,0.0002415141,0.000005480869,0.07053886,0.004150982,0.7396199,0.06966709,0.02075362,0.09037339],"study_design_scores_gemma":[0.003435449,0.00001334587,0.002886146,0.003645739,0.0003760911,0.00005303817,0.001045242,0.1062014,0.7773509,0.03007534,0.07161394,0.003303349],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3536965,0.0001156282,0.6192313,0.01377517,0.0004171527,0.00142535,0.0001545008,0.0002979325,0.01088643],"genre_scores_gemma":[0.8543482,0.00004652913,0.1414479,0.0005018684,0.00004299059,0.0005193466,0.0001320992,0.00005964304,0.002901406],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5006517,"threshold_uncertainty_score":0.9998066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02958489217375302,"score_gpt":0.2734088464919442,"score_spread":0.2438239543181912,"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."}}