{"id":"W3122317806","doi":"10.3390/nano11020283","title":"Homodyne Solid-State Biased Coherent Detection of Ultra-Broadband Terahertz Pulses with Static Electric Fields","year":2021,"lang":"en","type":"article","venue":"Nanomaterials","topic":"Terahertz technology and applications","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Ministère de l'Économie, de la Science et de l'Innovation - Québec","keywords":"Homodyne detection; Direct-conversion receiver; Terahertz radiation; Heterodyne (poetry); Physics; Heterodyne detection; Demodulation; Broadband; Optics; SIGNAL (programming language); Biasing; Dynamic range; Electronic engineering; Voltage; Electrical engineering; Engineering; Computer science; Channel (broadcasting); Acoustics; Laser","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.00005725557,0.0001382062,0.0002475051,0.0000825696,0.00005027836,0.00003080658,0.00009076017,0.0001094532,0.0001414047],"category_scores_gemma":[0.00001940152,0.0001229152,0.00003090802,0.0002814844,0.00002930384,0.00006823455,0.000007841586,0.00006801222,0.00001453703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002790008,"about_ca_system_score_gemma":0.00002702305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000141728,"about_ca_topic_score_gemma":0.00005124085,"domain_scores_codex":[0.9992477,0.0000306708,0.0002795161,0.0001621821,0.00008060072,0.0001993653],"domain_scores_gemma":[0.9995391,0.00005474878,0.00005885123,0.0002579591,0.00005676453,0.00003254649],"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":[0.00001996461,0.00004236518,0.0001334749,0.00007926521,0.00005644608,0.000008682019,0.00008531986,0.0002046692,0.9783764,0.00002585558,0.00005771702,0.0209098],"study_design_scores_gemma":[0.0003732966,0.00009096367,0.001745082,0.00003290778,0.00002890349,0.00003430506,0.00001796979,0.0003032311,0.9950555,0.0004304314,0.001744482,0.0001429372],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897002,0.0002157881,0.009152187,0.00004677027,0.000146285,0.0001988211,0.00003663008,0.0003063673,0.0001969371],"genre_scores_gemma":[0.9991804,0.00008648593,0.0004200169,0.00002126384,0.00002492538,0.0001203137,0.00002151707,0.00002536424,0.00009969119],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02076687,"threshold_uncertainty_score":0.5012337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006497501373607393,"score_gpt":0.2146061768999429,"score_spread":0.2081086755263355,"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."}}