{"id":"W4402473899","doi":"10.1109/tsp.2024.3459422","title":"DoA Estimation for Hybrid Receivers: Full Spatial Coverage and Successive Refinement","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Integrated Circuits and Semiconductor Failure Analysis","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ericsson (Canada); Carleton University; Ciena (Canada)","funders":"Mitacs","keywords":"Computer science; Algorithm; Signal processing; Estimation; Speech recognition; Mathematics; Telecommunications; Radar; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001012454,0.0007379776,0.0006924949,0.0006197852,0.0002201529,0.000665096,0.001032031,0.0007149071,0.0007672858],"category_scores_gemma":[0.004400765,0.0004291129,0.0007092502,0.0006761717,0.0007091117,0.001086549,0.001280011,0.0007141765,0.0003050655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003951866,"about_ca_system_score_gemma":0.000628209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002253511,"about_ca_topic_score_gemma":0.002741708,"domain_scores_codex":[0.9995498,0.0001154159,0.00002584107,0.00006619038,0.0002104685,0.00003226196],"domain_scores_gemma":[0.9983151,0.001079998,0.0001762419,0.0001931423,0.0001980628,0.00003745309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001864208,0.00004203164,0.001628694,0.0001410541,0.00009753023,0.00009424087,0.0002399556,0.7388994,0.01755738,0.02133482,0.0004969234,0.2192816],"study_design_scores_gemma":[0.00001176983,0.00003606446,0.0001792459,0.000007307204,0.000009377644,0.00004229325,0.000009007631,0.9936847,0.00231893,0.003139026,0.0005533589,0.000008964867],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004127053,0.00008705068,0.995336,0.00002114472,0.000006128926,0.000008109625,0.000008170759,0.00006611379,0.0003403076],"genre_scores_gemma":[0.2271013,0.0002871324,0.7711081,0.00006131285,0.00004268656,0.00008168029,0.00008031448,0.00003849072,0.001198961],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002253511,"threshold_uncertainty_score":0.005354464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01166813095375909,"score_gpt":0.2338378081609677,"score_spread":0.2221696772072086,"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."}}