{"id":"W2807731348","doi":"10.1109/tpwrd.2018.2846264","title":"Multiport Modular Multilevel Converter for DC Systems","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Power Delivery","topic":"HVDC Systems and Fault Protection","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Converters; Modular design; Control reconfiguration; Electronic engineering; Modularity (biology); Engineering; Scalability; Network topology; Reliability (semiconductor); Power (physics); Computer science; Interconnection; Electrical engineering; Voltage; Embedded system; Telecommunications","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":[0.0001078781,0.0002233448,0.0002323926,0.0003034495,0.0003027398,0.0005776596,0.0004308248,0.0003707535,0.00632798],"category_scores_gemma":[0.0002959148,0.00008284972,0.0002205519,0.0004393495,0.0001486327,0.0005612561,0.0002950094,0.0006632718,0.001076607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004232234,"about_ca_system_score_gemma":0.0002090877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002895184,"about_ca_topic_score_gemma":0.000589828,"domain_scores_codex":[0.9998845,0.00002307786,0.000005382376,0.00001619156,0.00006114245,0.000009778026],"domain_scores_gemma":[0.9999264,0.00001246889,0.00000970869,0.00001997477,0.00002688002,0.000004491152],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001259944,0.00007774078,0.0005173295,0.001057752,0.00007069029,0.0004825937,0.0002441187,0.04587977,0.1357184,0.3606444,0.0219275,0.4332539],"study_design_scores_gemma":[0.00007806299,0.0003049095,0.0008642035,0.0002245903,0.00006560287,0.001918167,0.0001062403,0.4454026,0.08036186,0.1066125,0.3640028,0.00005850887],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01899367,0.005592357,0.8885251,0.000989173,0.0004242005,0.0001848281,0.0002444927,0.00151993,0.08352634],"genre_scores_gemma":[0.7740316,0.00395756,0.2031274,0.0003431542,0.0002035838,0.000227206,0.0002497122,0.00008887306,0.01777099],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00632798,"threshold_uncertainty_score":0.02116925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01635079749869156,"score_gpt":0.2210475756768938,"score_spread":0.2046967781782023,"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."}}