{"id":"W2097523434","doi":"10.1109/icecs.1999.813200","title":"Adaptive beamforming in CDPD mobile end systems","year":2003,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Adaptive beamformer; Beamforming; Computer science; Digital radio; Channel (broadcasting); Antenna diversity; Electronic engineering; Antenna (radio); Smart antenna; Mobile telephony; Telecommunications; Mobile radio; Engineering; Directional antenna","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":[0.0003432625,0.0004949164,0.0002662153,0.0003147667,0.0002505116,0.0005390271,0.0002856679,0.0007978639,0.002179207],"category_scores_gemma":[0.001149472,0.0002287281,0.0001544164,0.0004971846,0.0004671058,0.0007378802,0.0004921493,0.0004490523,0.001044986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003079632,"about_ca_system_score_gemma":0.0002172223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008125702,"about_ca_topic_score_gemma":0.0008717456,"domain_scores_codex":[0.9996545,0.0001472684,0.00001259393,0.00005096005,0.0001065847,0.00002803082],"domain_scores_gemma":[0.9996533,0.0002125181,0.00002517564,0.00002167752,0.00007634295,0.00001094698],"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":[0.0002987864,0.00004200397,0.001348628,0.0001997005,0.00004127742,0.0004251664,0.0001789297,0.47877,0.105115,0.1078262,0.002576759,0.3031775],"study_design_scores_gemma":[0.00005736253,0.0002722457,0.0006563303,0.00004899374,0.00002650109,0.0005639954,0.0000870084,0.9119266,0.02617179,0.0462197,0.01392559,0.00004389999],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008798147,0.0005353786,0.9859917,0.000179556,0.00004509783,0.00001728528,0.00001871553,0.0001366071,0.004277541],"genre_scores_gemma":[0.5214779,0.002543796,0.4613866,0.0003977633,0.0001726855,0.0001228624,0.0000918459,0.00004742991,0.01375905],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002179207,"threshold_uncertainty_score":0.007290184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03105859594786642,"score_gpt":0.2806797359747294,"score_spread":0.249621140026863,"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."}}