{"id":"W4387870354","doi":"10.1109/iccworkshops57953.2023.10283500","title":"Active Beamforming for Integrated Sensing and Communication","year":2023,"lang":"en","type":"article","venue":"","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Beamforming; Computer science; Adaptive beamformer; Transmission (telecommunications); Focus (optics); Base station; Electronic engineering; Real-time computing; Telecommunications; 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":[],"consensus_categories":[],"category_scores_codex":[0.00004661363,0.00004248598,0.0000484957,0.00007572347,0.00006187821,0.0000151727,0.00003514313,0.00004351338,0.000002980794],"category_scores_gemma":[0.00004194226,0.00003819828,0.00000972478,0.0001749654,0.00001882795,0.00006329555,0.00001854295,0.00004149602,0.000005715783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001703363,"about_ca_system_score_gemma":0.000002323134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001290151,"about_ca_topic_score_gemma":0.00002765422,"domain_scores_codex":[0.9997944,0.000002646906,0.00005933983,0.00004119996,0.00002120351,0.00008117189],"domain_scores_gemma":[0.9998205,0.0000577708,0.000006110433,0.000081706,0.00002545818,0.000008500989],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001284726,0.000003611117,0.000114217,0.0001050366,0.00005751095,8.186944e-7,0.001954351,0.01599966,0.01524151,0.01897197,0.007545425,0.939993],"study_design_scores_gemma":[0.0001453103,0.00000774242,0.0001080423,0.00001656548,0.000004379098,0.00000147396,0.003045384,0.8703439,0.1146968,0.002880725,0.008666866,0.00008273553],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1817772,0.00005916565,0.8080887,0.0002237672,0.00009509983,0.0002489917,0.000009982442,0.004077251,0.005419926],"genre_scores_gemma":[0.9873484,0.0001131428,0.01228661,0.00001923985,0.000005336865,0.000006705474,0.00004490003,0.00001243132,0.0001632795],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9399103,"threshold_uncertainty_score":0.1557681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0132308457307042,"score_gpt":0.2324226180434367,"score_spread":0.2191917723127325,"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."}}