{"id":"W2328178685","doi":"10.1109/intlec.2014.6972168","title":"High voltage, high power, high efficiency, digitally-controlled LLC converter for telecom applications","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced DC-DC Converters","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alpha Technologies (Canada)","funders":"","keywords":"Rectifier (neural networks); Electronic engineering; Voltage; Computer science; Microcontroller; Network topology; Electrical engineering; Filter (signal processing); Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002285501,0.0001598125,0.0001963986,0.0001965691,0.0002328102,0.0004079996,0.0003701078,0.0002825325,0.002116907],"category_scores_gemma":[0.0002409326,0.00009347731,0.0001517191,0.0002803048,0.0001640912,0.0004838915,0.0001874286,0.0004771599,0.0009234485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001966617,"about_ca_system_score_gemma":0.0002587395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001234574,"about_ca_topic_score_gemma":0.0003908251,"domain_scores_codex":[0.9998019,0.00002694736,0.00001016981,0.00002236779,0.0001262714,0.00001239528],"domain_scores_gemma":[0.9998797,0.00002850907,0.00001408531,0.0000193192,0.00005128349,0.000007117703],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001386343,0.0001141676,0.0008153219,0.0003992951,0.00001755486,0.0003064946,0.0001758404,0.006583982,0.6358016,0.01487433,0.002617212,0.3381556],"study_design_scores_gemma":[0.0001745653,0.001634176,0.003622914,0.00009651632,0.00005872429,0.003778226,0.0001275431,0.1563769,0.6905558,0.007924262,0.1355994,0.00005102484],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06075733,0.0008133831,0.9108144,0.000222831,0.0001018895,0.0001160953,0.00006605462,0.0009636299,0.02614436],"genre_scores_gemma":[0.7026293,0.0007419852,0.2754199,0.000166648,0.0001091893,0.00009934045,0.0001291693,0.00013516,0.02056932],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002116907,"threshold_uncertainty_score":0.007081807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003040445421642139,"score_gpt":0.1910895102822798,"score_spread":0.1880490648606376,"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."}}