{"id":"W2558353860","doi":"10.1109/iemcon.2016.7746238","title":"Direction of Arrival algorithms for user identification in cellular networks","year":2016,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Algorithm; Direction of arrival; Computer science; Angle of arrival; SIGNAL (programming language); Transmitter; Interference (communication); Identification (biology); Multiple signal classification; Projection (relational algebra); Telecommunications; 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":[0.001163844,0.001061475,0.0007122732,0.001478806,0.0006602511,0.001161162,0.0009610916,0.0009997655,0.00264824],"category_scores_gemma":[0.005756114,0.0002985118,0.0005472638,0.002071509,0.0005088448,0.001574902,0.0009430907,0.00153127,0.002051377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005202633,"about_ca_system_score_gemma":0.0009937874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002192573,"about_ca_topic_score_gemma":0.00192932,"domain_scores_codex":[0.9989578,0.0004037904,0.00005587933,0.0001204768,0.0003857976,0.00007626924],"domain_scores_gemma":[0.9986357,0.0005317171,0.0001111011,0.0002037073,0.0004845587,0.00003330323],"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":[0.0002035917,0.00007378645,0.001748057,0.0001808164,0.00005906362,0.00009364264,0.0001188253,0.2293211,0.007202586,0.07292331,0.007679172,0.6803961],"study_design_scores_gemma":[0.00003991033,0.00008629252,0.0006249018,0.00004086496,0.00001913277,0.0002196748,0.00007044978,0.9432729,0.004307774,0.03759025,0.01368769,0.00004025701],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001723858,0.0007918893,0.9954476,0.00007942895,0.00009082974,0.00003512156,0.00004216199,0.0004167785,0.001372346],"genre_scores_gemma":[0.1097806,0.002340417,0.8828735,0.0001648497,0.0002332806,0.0002845349,0.0003736063,0.0001329061,0.003816316],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00264824,"threshold_uncertainty_score":0.008859217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01748276120721316,"score_gpt":0.2711198178736047,"score_spread":0.2536370566663915,"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."}}