{"id":"W2335398026","doi":"10.1049/el.2016.0717","title":"Orthogonal polynomials non‐linearity compensation for a digital VCO‐based ADC","year":2016,"lang":"en","type":"article","venue":"Electronics Letters","topic":"Analog and Mixed-Signal Circuit Design","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Voltage-controlled oscillator; Linearity; Electronic engineering; Orthogonal polynomials; Compensation (psychology); Computer science; Mathematics; Electrical engineering; Engineering; Voltage; Psychology","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":[0.0001919189,0.0003203218,0.0002298992,0.0003490918,0.0002894494,0.0003646926,0.0005190941,0.0003567308,0.001043937],"category_scores_gemma":[0.0004930571,0.0001801645,0.0001739444,0.0003727601,0.0002021541,0.0004250647,0.0002323106,0.0005011552,0.0002758903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004100099,"about_ca_system_score_gemma":0.0005183279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001229024,"about_ca_topic_score_gemma":0.003019188,"domain_scores_codex":[0.9997248,0.00003331482,0.00001255399,0.00004144184,0.0001663026,0.00002164507],"domain_scores_gemma":[0.9998325,0.0000370047,0.00002453837,0.00002403415,0.00007114181,0.00001074139],"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":[0.0001930287,0.00005467957,0.0004733921,0.0001078144,0.00003396019,0.00009943754,0.00008064926,0.01141825,0.6784592,0.008507523,0.001047391,0.2995248],"study_design_scores_gemma":[0.00004450484,0.0001770387,0.001108038,0.00001788432,0.0000548645,0.0004456993,0.00001845673,0.502778,0.4827301,0.0009828468,0.01159292,0.00004970839],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06324888,0.0005047815,0.9322492,0.0001443123,0.0001563928,0.00003398845,0.00003159271,0.0005950123,0.00303574],"genre_scores_gemma":[0.6003838,0.0004411014,0.3930657,0.0001048441,0.0001077195,0.00002973683,0.00006756594,0.00004724606,0.005752325],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001229024,"threshold_uncertainty_score":0.003492355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008621675197565558,"score_gpt":0.1954123339082156,"score_spread":0.18679065871065,"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."}}