{"id":"W4364383164","doi":"10.1109/jstqe.2023.3266276","title":"Quantifying the Accuracy of Microcomb-Based Photonic RF Transversal Signal Processors","year":2023,"lang":"en","type":"article","venue":"IEEE Journal of Selected Topics in Quantum Electronics","topic":"Advanced Fiber Laser Technologies","field":"Physics and Astronomy","cited_by":106,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Photonics; Radio frequency; Transversal (combinatorics); Optoelectronics; Signal processing; Computer science; SIGNAL (programming language); Optics; Materials science; Physics; Telecommunications; Digital signal processing; Computer hardware","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":[0.0004391023,0.0002411976,0.0004549933,0.0003633362,0.0001137674,0.00003285727,0.0007497002,0.0001175989,0.00002602657],"category_scores_gemma":[0.00009108924,0.0001874313,0.000185071,0.001967902,0.0001299184,0.0002194644,0.00002420907,0.001278672,0.000003529634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001292818,"about_ca_system_score_gemma":0.0008828079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002219957,"about_ca_topic_score_gemma":0.00004508442,"domain_scores_codex":[0.9979007,0.00007950824,0.0008211336,0.0002011539,0.0003690044,0.0006285419],"domain_scores_gemma":[0.9980717,0.0004096401,0.0007454218,0.0002511261,0.0004774788,0.00004459777],"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":[0.0007915992,0.000935538,0.03995493,0.0003431476,0.0007161773,0.00006847658,0.002094007,0.08815081,0.8038563,0.02492708,0.001096464,0.03706545],"study_design_scores_gemma":[0.002001532,0.0006262333,0.00163244,0.0002078882,0.00009190913,0.00001354637,0.0007435781,0.02550504,0.9463736,0.01946803,0.002989499,0.0003466568],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903873,0.0006162942,0.007569801,0.0009136035,0.0001522601,0.0002499423,0.00001014159,0.00006067078,0.00004000591],"genre_scores_gemma":[0.9990694,0.0001606753,0.0005323452,0.00003175711,0.000128762,0.00001303817,0.000006508479,0.00003355827,0.00002399031],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1425173,"threshold_uncertainty_score":0.7643228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02329624931136282,"score_gpt":0.2901195492898002,"score_spread":0.2668232999784374,"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."}}