{"id":"W4386915003","doi":"10.36227/techrxiv.24153384","title":"Noise Shaping for Phased Array with Overlapped Sub-Array System","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Antenna Design and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; Institut National de la Recherche Scientifique","funders":"","keywords":"Beamforming; Phased array; Phased-array optics; Superposition principle; Computer science; Quantization (signal processing); Distortion (music); Acoustics; Electronic engineering; Optics; Telecommunications; Bandwidth (computing); Physics; Engineering; Algorithm","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":[0.0002060109,0.0005770323,0.0003349009,0.0002079628,0.0002311073,0.0004317393,0.0004410637,0.0004565093,0.002115643],"category_scores_gemma":[0.0006795586,0.000211258,0.0003052893,0.0004221222,0.0003392492,0.0005038542,0.0005156809,0.0003247775,0.0006449125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004277126,"about_ca_system_score_gemma":0.0003525068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006198742,"about_ca_topic_score_gemma":0.0009897,"domain_scores_codex":[0.9996567,0.0000750086,0.00001452082,0.0000672467,0.0001579436,0.00002862707],"domain_scores_gemma":[0.999757,0.00007836845,0.00004376541,0.00003751935,0.00007096697,0.00001246105],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004229858,0.00006765347,0.0008562769,0.0002887238,0.00008972909,0.0001980059,0.0002574244,0.4413857,0.2456904,0.04285877,0.002863808,0.2650206],"study_design_scores_gemma":[0.0000166377,0.00009743818,0.0001622949,0.00001342586,0.00001603365,0.0001094546,0.00002205105,0.9721999,0.01883794,0.004372023,0.004138081,0.00001472858],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009508467,0.0001926158,0.9867113,0.00007001402,0.00003376773,0.00001409807,0.00002509974,0.0001769937,0.003267697],"genre_scores_gemma":[0.571785,0.0006772958,0.4189607,0.0002322152,0.0001128616,0.0001140807,0.0001288063,0.00007975615,0.007909228],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002115643,"threshold_uncertainty_score":0.007077515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03802022421989478,"score_gpt":0.2313611841575801,"score_spread":0.1933409599376854,"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."}}