{"id":"W4401420094","doi":"10.1103/physrevapplied.22.024025","title":"Kinetic inductance parametric converter","year":2024,"lang":"en","type":"article","venue":"Physical Review Applied","topic":"Sensor Technology and Measurement Systems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Stewart Blusson Quantum Matter Institute, University of British Columbia; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Canada Foundation for Innovation","keywords":"Kinetic energy; Parametric statistics; Inductance; Kinetic inductance; Physics; Mathematics; Classical mechanics; Voltage; Statistics","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":[0.0001086584,0.0002142533,0.0002178566,0.0001833487,0.0003672479,0.0007587188,0.0005947542,0.0003477567,0.00414813],"category_scores_gemma":[0.0003785298,0.0001488639,0.0001273973,0.0002587731,0.0003434545,0.001001472,0.0004264861,0.0005266159,0.001371891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005256002,"about_ca_system_score_gemma":0.0002474699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002588984,"about_ca_topic_score_gemma":0.0003610432,"domain_scores_codex":[0.9998654,0.000008671233,0.000007243538,0.00003854496,0.00006284913,0.0000172923],"domain_scores_gemma":[0.9998391,0.00003492265,0.00002823184,0.00003584091,0.00004428025,0.00001758648],"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":[0.0001495467,0.00006924617,0.0005948409,0.0002240518,0.00001713558,0.0002508579,0.0001572093,0.00183229,0.8839288,0.05483516,0.00281997,0.0551209],"study_design_scores_gemma":[0.00003097271,0.0002040592,0.0008594351,0.00002307558,0.00002779751,0.001083622,0.00006336535,0.03615925,0.8972721,0.0060382,0.05819569,0.00004236796],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4809223,0.003385373,0.3601744,0.001415113,0.0007009656,0.0002463715,0.000843178,0.003157005,0.1491552],"genre_scores_gemma":[0.9447381,0.0005466017,0.03701089,0.0001569266,0.00005188816,0.00007363263,0.0001618791,0.00008249822,0.01717761],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00414813,"threshold_uncertainty_score":0.01387686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03130239415611399,"score_gpt":0.2887949261105747,"score_spread":0.2574925319544606,"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."}}