{"id":"W2559355139","doi":"10.5539/apr.v8n6p101","title":"Magnetic Coupling in Tesla transformers","year":2016,"lang":"en","type":"article","venue":"Applied Physics Research","topic":"Pulsed Power Technology Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transformer; Electromagnetic coil; Inductive coupling; Computer science; Electrical engineering; Physics; Nuclear magnetic resonance; Voltage; Engineering","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":[0.0003918942,0.0003710109,0.0004010884,0.0005111726,0.0005274885,0.001212851,0.0004913232,0.0004705021,0.005358432],"category_scores_gemma":[0.00171407,0.0003206224,0.0002109271,0.0006668526,0.0005072114,0.001121661,0.0007491947,0.000593324,0.001460345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005435772,"about_ca_system_score_gemma":0.0003074475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000493406,"about_ca_topic_score_gemma":0.000372144,"domain_scores_codex":[0.999499,0.0001444947,0.00002098112,0.0000808678,0.0001913134,0.00006339304],"domain_scores_gemma":[0.9995258,0.0002003163,0.00007596365,0.00007378648,0.00009638938,0.00002775347],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001028716,0.0001216222,0.002685566,0.0007391857,0.00006582386,0.0009613227,0.001582411,0.02222916,0.3437448,0.4599219,0.007963378,0.1589562],"study_design_scores_gemma":[0.0001165993,0.001295763,0.005655231,0.0003467886,0.0001478896,0.007317324,0.0008496546,0.1656826,0.4839834,0.1320173,0.2024442,0.0001432352],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2554336,0.00423242,0.5387371,0.0006195733,0.0004139022,0.0001254672,0.0001854132,0.003272604,0.1969798],"genre_scores_gemma":[0.9523922,0.001013403,0.02388798,0.0001339743,0.00007373523,0.00005281745,0.00009982297,0.0002819668,0.02206413],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005358432,"threshold_uncertainty_score":0.01792574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02857316358794434,"score_gpt":0.3026872657151495,"score_spread":0.2741141021272052,"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."}}