{"id":"W4386789488","doi":"10.53555/sfs.v10i2s.330","title":"Design of 243 Level Trinary Ladder Multilevel Inverter using VHDL","year":2023,"lang":"en","type":"article","venue":"Journal of Survey in Fisheries Sciences","topic":"Multilevel Inverters and Converters","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Inverter; Computer science; VHDL; Pulse-width modulation; MATLAB; Total harmonic distortion; Electronic engineering; Control theory (sociology); Topology (electrical circuits); Engineering; Computer hardware; Voltage; Field-programmable gate array; Control (management); Electrical engineering; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000101355,0.0002009471,0.0002448778,0.0002624885,0.0002147565,0.0006082982,0.0005997187,0.0002612827,0.004722966],"category_scores_gemma":[0.0001692719,0.0001293744,0.0002620391,0.0002073565,0.0001039606,0.000265295,0.0002387561,0.0003242018,0.0008397596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003680979,"about_ca_system_score_gemma":0.0003392227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001184295,"about_ca_topic_score_gemma":0.001573794,"domain_scores_codex":[0.9998584,0.00001728606,0.00001200111,0.00002229909,0.00007229123,0.000017599],"domain_scores_gemma":[0.9999366,0.000008672494,0.00001162857,0.000009236084,0.00002985656,0.000004004493],"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":[0.000294941,0.0002046054,0.002677165,0.001063106,0.0001727332,0.0007668106,0.0004678964,0.2237284,0.2882435,0.04065364,0.00706396,0.4346632],"study_design_scores_gemma":[0.0001143283,0.0005511564,0.0015001,0.0001061344,0.0001018618,0.000678728,0.00009740198,0.8026639,0.112931,0.007349659,0.07385329,0.00005245856],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03400818,0.0002628824,0.9414539,0.0001260418,0.00007704407,0.0001739323,0.0002289943,0.002439652,0.02122949],"genre_scores_gemma":[0.7492663,0.0003584797,0.239813,0.0001217121,0.0000247962,0.0002811398,0.0005000797,0.0001328803,0.009501631],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004722966,"threshold_uncertainty_score":0.01579988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.498985700642588,"score_gpt":0.3032198660984542,"score_spread":0.1957658345441337,"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."}}