{"id":"W4391920817","doi":"10.1038/s41467-024-45743-9","title":"Ultrabroadband high-resolution silicon RF-photonic beamformer","year":2024,"lang":"en","type":"article","venue":"Nature Communications","topic":"Advanced Photonic Communication Systems","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"Broadband; Photonics; Bandwidth (computing); Computer science; Silicon photonics; True time delay; Beamforming; Electronic engineering; Optics; Telecommunications; Optoelectronics; Materials science; Physics; Phased array; Engineering; Antenna (radio)","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":[0.0002352885,0.0003566133,0.0002090726,0.0002272794,0.0001271564,0.00039544,0.0004308967,0.0004778548,0.003179875],"category_scores_gemma":[0.0002975525,0.0001883129,0.0001256756,0.0002407324,0.0003316654,0.0005046242,0.000333821,0.0002986925,0.001043384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004567983,"about_ca_system_score_gemma":0.000398126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000382589,"about_ca_topic_score_gemma":0.001126637,"domain_scores_codex":[0.9998378,0.00002730994,0.000008762768,0.00003544358,0.00007060874,0.00002014133],"domain_scores_gemma":[0.9996907,0.00008905552,0.0000837383,0.00002541366,0.00008669523,0.00002443957],"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":[0.0001292486,0.00002910964,0.0002395212,0.00003924916,0.00001574293,0.00007127156,0.00002766606,0.004710805,0.9713966,0.002905977,0.0006007742,0.01983412],"study_design_scores_gemma":[0.0000784445,0.0004096947,0.001076593,0.00001816575,0.0000255963,0.0004762714,0.00003582164,0.1216273,0.8617812,0.001032871,0.01339792,0.00004012602],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1566925,0.0004775498,0.8295215,0.000468604,0.0001727445,0.00006954096,0.0001966409,0.001431796,0.01096915],"genre_scores_gemma":[0.6919966,0.0002219234,0.3014238,0.0002332685,0.00005921952,0.00004144278,0.0001399081,0.00004736247,0.005836424],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003179875,"threshold_uncertainty_score":0.01063776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01342387403078895,"score_gpt":0.2791968919181715,"score_spread":0.2657730178873826,"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."}}