{"id":"W4386634537","doi":"10.1109/jlt.2023.3314526","title":"Optimizing the Accuracy of Microcomb-Based Microwave Photonic Transversal Signal Processors","year":2023,"lang":"en","type":"article","venue":"Journal of Lightwave Technology","topic":"Advanced Photonic Communication Systems","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Swinburne University of Technology","keywords":"Signal processing; Computer science; Photonics; Electronic engineering; SIGNAL (programming language); Chirp; Digital signal processing; Bandwidth (computing); Optics; Physics; Computer hardware; Telecommunications; Engineering; Laser","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004580424,0.0001770395,0.0004167818,0.0006619925,0.00007231108,0.00001381148,0.0009969382,0.0001919518,0.00003044019],"category_scores_gemma":[0.00008169838,0.0001338287,0.000170903,0.001238865,0.000181111,0.0001236962,0.00005780828,0.0006721393,0.00001602186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001109636,"about_ca_system_score_gemma":0.0001273474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001562092,"about_ca_topic_score_gemma":0.000007198893,"domain_scores_codex":[0.9985201,0.00004460797,0.0008169478,0.0001061848,0.0002232725,0.0002888424],"domain_scores_gemma":[0.9984089,0.000352652,0.0004801707,0.0004818908,0.0002326622,0.00004375951],"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":[0.00004063058,0.00003406499,0.00008361288,0.0001222396,0.0001518726,0.00002667248,0.0009443267,0.03627041,0.9580272,0.0002651602,0.0005049594,0.003528875],"study_design_scores_gemma":[0.0009031264,0.0001277652,0.00003748149,0.0002081271,0.00004387899,0.0001875808,0.0009334589,0.01482431,0.9610301,0.0007727711,0.02077023,0.000161236],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9479987,0.004738654,0.04169389,0.002893067,0.0004372398,0.000595492,0.00001507384,0.0006571721,0.0009706936],"genre_scores_gemma":[0.9922603,0.000294474,0.007306892,0.0000245923,0.00002852068,0.00001764946,0.000001691619,0.00004097997,0.00002494055],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04426154,"threshold_uncertainty_score":0.5457375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01459200748116745,"score_gpt":0.2515108192490825,"score_spread":0.236918811767915,"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."}}