{"id":"W1975389390","doi":"10.1117/12.551019","title":"Low-noise InP HEMT amplifier","year":2004,"lang":"de","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Superconducting and THz Device Technology","field":"Physics and Astronomy","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Herzberg Institute of Astrophysics","funders":"National Radio Astronomy Observatory","keywords":"Preamplifier; Amplifier; Low-noise amplifier; Instrumentation amplifier; Y-factor; Noise temperature; Electrical engineering; Effective input noise temperature; High-electron-mobility transistor; Noise figure; Impedance matching; Return loss; Optoelectronics; Materials science; Electronic engineering; Physics; RF power amplifier; Engineering; Electrical impedance; Transistor; Phase noise; Antenna (radio); 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":[0.0001039804,0.0002149957,0.00022826,0.0001215429,0.0003133478,0.0004658605,0.0006348929,0.0003299919,0.002505579],"category_scores_gemma":[0.0002316509,0.0001398205,0.0001510166,0.00009344495,0.0001895964,0.0003900695,0.0002202125,0.0004536469,0.00149371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004125625,"about_ca_system_score_gemma":0.0002999688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004564681,"about_ca_topic_score_gemma":0.0009723989,"domain_scores_codex":[0.9998399,0.00001026788,0.000004823986,0.00002676398,0.00009626659,0.00002196943],"domain_scores_gemma":[0.9999193,0.00001300744,0.00001196627,0.000009078974,0.00003605838,0.00001054932],"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":[0.00005126364,0.0000183052,0.0005899939,0.00006191257,0.000009581633,0.0002235319,0.0001211561,0.001171939,0.9733439,0.00241787,0.0009986287,0.02099188],"study_design_scores_gemma":[0.00002181561,0.0004087324,0.002740374,0.0000193543,0.00003783737,0.001550685,0.00006604745,0.02726528,0.9382656,0.001084754,0.02851452,0.00002503742],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3931582,0.0009726927,0.5470091,0.0009584184,0.0002979349,0.0002017736,0.0003061911,0.003090016,0.05400576],"genre_scores_gemma":[0.8515785,0.0004423793,0.1254057,0.000213255,0.0001051165,0.00007544105,0.0001798015,0.000180623,0.02181916],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002505579,"threshold_uncertainty_score":0.008381963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01118341524096087,"score_gpt":0.229480363175827,"score_spread":0.2182969479348661,"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."}}