{"id":"W4393106436","doi":"10.1109/tpel.2024.3380570","title":"Γ-Type Five-Level Current Source Inverter","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Power Electronics","topic":"Multilevel Inverters and Converters","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Current (fluid); Inverter; Electrical engineering; Current source; Computer science; Grid-tie inverter; Electronic engineering; Engineering; Voltage; Maximum power point tracking","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":[0.00008833079,0.0003215806,0.0003614722,0.0003107094,0.0002294527,0.0007643856,0.000971348,0.0003220123,0.004752168],"category_scores_gemma":[0.0001753634,0.0001177582,0.0002783009,0.0005271811,0.0001671947,0.0007528071,0.0004649149,0.0004340867,0.001327481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003186782,"about_ca_system_score_gemma":0.000288299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004505081,"about_ca_topic_score_gemma":0.0006627644,"domain_scores_codex":[0.9998713,0.000008629885,0.00001123087,0.00002959641,0.00006305657,0.000016251],"domain_scores_gemma":[0.9999094,0.000008808541,0.0000198202,0.00001349464,0.00003757427,0.00001094638],"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":[0.0004790391,0.0001722783,0.001634423,0.001259705,0.0001263795,0.0004684637,0.000380627,0.03018803,0.4535052,0.1015697,0.006171758,0.4040444],"study_design_scores_gemma":[0.0002049015,0.002080107,0.004484948,0.0002747175,0.0002270802,0.001649332,0.0002734335,0.4071282,0.4034071,0.04128666,0.138844,0.0001395863],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07578629,0.0007090848,0.8571852,0.0001863687,0.0001667666,0.000175949,0.0004991823,0.001964829,0.06332637],"genre_scores_gemma":[0.9043995,0.000748919,0.0800137,0.0002748458,0.00003814512,0.0000835162,0.0005069203,0.0000639661,0.01387043],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004752168,"threshold_uncertainty_score":0.01589757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01762176137856624,"score_gpt":0.2363689423673007,"score_spread":0.2187471809887344,"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."}}