{"id":"W4239506917","doi":"10.1142/9789812774583_0003","title":"HIGH-SPEED OVERSAMPLING ANALOG-TO-DIGITAL CONVERTERS","year":2006,"lang":"en","type":"book-chapter","venue":"Selected topics in electornics and systems","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Oversampling; Converters; Computer science; Electronic engineering; Electrical engineering; Engineering; Telecommunications; Bandwidth (computing); Voltage","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009767984,0.0003357029,0.0004846169,0.0002339003,0.0001077921,0.0005118141,0.0005194853,0.0002955699,0.000003513237],"category_scores_gemma":[0.00001200344,0.0003365758,0.00006185945,0.000310689,0.00002921097,0.0001325806,0.0001407864,0.0004638983,0.00002036253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001402481,"about_ca_system_score_gemma":0.00009863943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001731038,"about_ca_topic_score_gemma":0.000102846,"domain_scores_codex":[0.9981077,0.00001657858,0.0005101341,0.0006814039,0.0002768933,0.0004072767],"domain_scores_gemma":[0.9989172,0.00009458059,0.0001878972,0.0004922164,0.000173211,0.0001349424],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006156513,0.00002656702,0.0003574133,0.00007048267,0.00006933331,0.00003615564,0.00006135664,0.002544724,0.0001743984,0.9748493,0.01379828,0.00800582],"study_design_scores_gemma":[0.000980765,0.0003718413,0.00117072,0.0005969997,0.00004613578,0.00009903622,0.000005841991,0.1903565,0.00004868926,0.03651837,0.7677549,0.002050237],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02397337,0.01160373,0.5546143,0.003399643,0.00874522,0.007794682,0.0005661587,0.00198729,0.3873156],"genre_scores_gemma":[0.8077742,0.0003083301,0.001056452,0.0003917764,0.001527104,0.00004383696,0.0002988997,0.0001152819,0.1884841],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9383309,"threshold_uncertainty_score":0.9999086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01483471470418871,"score_gpt":0.2146661635696066,"score_spread":0.1998314488654179,"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."}}