{"id":"W2540383318","doi":"10.1109/bmn.2006.330883","title":"A genetic differential amplifier: design, simulation, construction, and testing","year":2006,"lang":"en","type":"article","venue":"","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Amplifier; Lambda; Computer science; Topology (electrical circuits); Physics; Mathematics; Combinatorics; Bandwidth (computing); Telecommunications","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":[0.0004345727,0.0005112567,0.0003166183,0.0003763461,0.0002707047,0.0007041214,0.001135802,0.0005814243,0.01138684],"category_scores_gemma":[0.001233643,0.00023176,0.000219665,0.0003784697,0.0002801543,0.0005599879,0.0003236682,0.0003922878,0.003421863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005979537,"about_ca_system_score_gemma":0.0005126316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001046775,"about_ca_topic_score_gemma":0.001041692,"domain_scores_codex":[0.9996082,0.00005787097,0.00001949043,0.00005736096,0.0002341105,0.00002288749],"domain_scores_gemma":[0.9994853,0.0001419025,0.00004111183,0.00006501572,0.0002443004,0.00002241432],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007028144,0.0001725062,0.005430098,0.001634625,0.0001416478,0.0005649122,0.0004178615,0.2292703,0.2621261,0.02645068,0.03415951,0.4389289],"study_design_scores_gemma":[0.00008996879,0.0007207413,0.001491691,0.0001052362,0.0001263454,0.000532063,0.00008823697,0.6388347,0.2218523,0.004244088,0.1318526,0.00006197161],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03016419,0.0008018003,0.9322894,0.0005219586,0.0002967051,0.0005052044,0.000851676,0.007831273,0.02673783],"genre_scores_gemma":[0.6012969,0.001300373,0.3566192,0.0002365802,0.00009393596,0.00110628,0.001502717,0.001041091,0.03680307],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01138684,"threshold_uncertainty_score":0.03809279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02375303329294081,"score_gpt":0.2687403671917264,"score_spread":0.2449873338987856,"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."}}