{"id":"W1995759967","doi":"10.1109/tnb.2003.820283","title":"A genetic circuit amplifier: design and simulation","year":2003,"lang":"en","type":"article","venue":"IEEE Transactions on NanoBioscience","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Discrete circuit; Linear circuit; Amplifier; Circuit extraction; Computer science; Equivalent circuit; Electronic circuit simulation; RL circuit; Electronic engineering; Circuit design; Capacitor; Electrical element; Electronic circuit; RC circuit; Electrical engineering; Engineering; Voltage; CMOS","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":[0.000201175,0.0003026743,0.0003072218,0.0003027364,0.0002869236,0.0005624855,0.0009006445,0.0008238457,0.003585161],"category_scores_gemma":[0.0004501579,0.0002161369,0.0002721951,0.0002677548,0.0003081776,0.0003503758,0.0002706458,0.0003713515,0.0007022119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006179862,"about_ca_system_score_gemma":0.0006508987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0023894,"about_ca_topic_score_gemma":0.001538555,"domain_scores_codex":[0.9998674,0.00002440615,0.000004964032,0.00001920311,0.00006586753,0.00001805528],"domain_scores_gemma":[0.9998869,0.00004031455,0.00001265803,0.00001282841,0.00003741064,0.000009852352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006033574,0.0000445523,0.0005692466,0.0001419845,0.00002335045,0.0001440151,0.00005546871,0.9316598,0.02539581,0.01767332,0.001058694,0.02317346],"study_design_scores_gemma":[0.00001397423,0.00004878924,0.00009941809,0.000006952203,0.000008157186,0.00004165264,0.000007470848,0.988684,0.005436377,0.001558411,0.004088606,0.000006117601],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07111473,0.0003890455,0.8960711,0.0004411881,0.00008027488,0.000355417,0.000332845,0.002063725,0.02915166],"genre_scores_gemma":[0.6700826,0.0004528346,0.3149226,0.000110461,0.0000238304,0.0008779743,0.0002344028,0.0001402649,0.01315505],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003585161,"threshold_uncertainty_score":0.01199353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01897900654593569,"score_gpt":0.2403111037572923,"score_spread":0.2213320972113567,"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."}}