{"id":"W3210260041","doi":"10.1109/jsac.2022.3196320","title":"Antenna Array Enabled Space/Air/Ground Communications and Networking for 6G","year":2022,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Communications","topic":"Antenna Design and Analysis","field":"Engineering","cited_by":121,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada); Memorial University of Newfoundland","funders":"Natural Science Foundation of Beijing Municipality; National Natural Science Foundation of China","keywords":"Computer science; Beamforming; Telecommunications; Wireless; Communications system; Antenna array; Antenna (radio); Electronic engineering; Electrical engineering; Engineering","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0005681875,0.0001819761,0.0002920815,0.0003681084,0.001403538,0.0001002483,0.001157012,0.0000588892,0.00002233157],"category_scores_gemma":[0.00005472406,0.0002003908,0.0001067985,0.001267279,0.00009781267,0.0001466637,0.0001447769,0.001214858,0.000004032328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002934437,"about_ca_system_score_gemma":0.00009722883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001703003,"about_ca_topic_score_gemma":0.0002545321,"domain_scores_codex":[0.9984499,0.0004021506,0.0004747006,0.0001474867,0.0001857467,0.0003400637],"domain_scores_gemma":[0.9973634,0.0008186228,0.0001449821,0.001338787,0.0002177306,0.0001165079],"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":[0.0007781019,0.005743056,0.03816006,0.0003024147,0.005465879,0.0001277423,0.01721642,0.06369922,0.7468354,0.02586525,0.04039763,0.05540884],"study_design_scores_gemma":[0.001873033,0.0002278179,0.003051456,0.0002157455,0.0002381049,0.0005048829,0.00202524,0.7811152,0.0002026242,0.00587642,0.2039378,0.0007316802],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.162492,0.1122184,0.6260388,0.06261336,0.004242723,0.003782366,0.0005969013,0.00230407,0.02571132],"genre_scores_gemma":[0.9808896,0.01188015,0.006311751,0.0002701686,0.0001345933,0.0001494271,0.00006599143,0.00005115081,0.0002471859],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8183976,"threshold_uncertainty_score":0.9998965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03539496937769199,"score_gpt":0.2672172714907967,"score_spread":0.2318223021131047,"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."}}