{"id":"W4390725418","doi":"10.1038/s41377-023-01362-5","title":"A system-on-chip microwave photonic processor solves dynamic RF interference in real time with picosecond latency","year":2024,"lang":"en","type":"article","venue":"Light Science & Applications","topic":"Advanced Photonic Communication Systems","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Division of Electrical, Communications and Cyber Systems; Office of Naval Research; Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; CMC Microsystems; Defense Advanced Research Projects Agency; Advanced Research Projects Agency; National Science Foundation; Government of Canada; U.S. Department of Defense","keywords":"Picosecond; Latency (audio); Microwave; Computer science; Photonics; Chip; Interference (communication); Optoelectronics; Electronic engineering; Optics; Telecommunications; Physics; Engineering; 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":[0.0002874774,0.0002061565,0.0002032912,0.0003883846,0.0001665832,0.0001797132,0.0009500966,0.00005686396,0.00002485854],"category_scores_gemma":[0.000006909027,0.0001762892,0.00003263597,0.001942621,0.0002166151,0.0003349984,0.0000676236,0.000278543,0.0003976221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005400972,"about_ca_system_score_gemma":0.0002724041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001502429,"about_ca_topic_score_gemma":0.0001409236,"domain_scores_codex":[0.998508,0.00001419181,0.0003616998,0.0005105134,0.0002355756,0.0003700083],"domain_scores_gemma":[0.9987265,0.0001038677,0.00005391551,0.0009359922,0.00007494145,0.000104723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001417778,0.0001110872,0.0001143541,0.0007031058,0.00002528175,0.000007994389,0.002797868,0.01291775,0.9540873,0.02347647,0.00006622716,0.005678438],"study_design_scores_gemma":[0.0004297331,0.0001332838,0.0008188997,0.001995301,0.00002755017,0.00009356291,0.0008750541,0.8719632,0.1106884,0.001725046,0.01037328,0.0008767478],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5906818,0.003019507,0.1210878,0.0008276193,0.0004084869,0.005367623,0.0001211845,0.004191836,0.2742942],"genre_scores_gemma":[0.9957703,0.00004172534,0.002031205,0.00001275461,0.00001410439,0.001747172,0.00001071803,0.00003530678,0.0003366683],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8590454,"threshold_uncertainty_score":0.7188867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008087189977327547,"score_gpt":0.2482682642694499,"score_spread":0.2401810742921223,"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."}}