{"id":"W2060012946","doi":"10.1109/iscas.2013.6572308","title":"An approach for joint blind space-time equalization and DOA estimation","year":2013,"lang":"en","type":"article","venue":"","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Joint (building); Interference (communication); Fading; Algorithm; Blind equalization; Equalization (audio); Control theory (sociology); Sequence (biology); SIGNAL (programming language); Constant (computer programming); Property (philosophy); Channel (broadcasting); Telecommunications; Artificial intelligence; 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":[0.0003408166,0.0000788109,0.00008821233,0.0001054676,0.00007891779,0.0004187589,0.0001651775,0.00006141561,0.00002353728],"category_scores_gemma":[0.00003002388,0.00006794162,0.00001774773,0.0001347015,0.00001940948,0.001183511,0.00004395409,0.00003346976,0.0000224001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001254268,"about_ca_system_score_gemma":0.00001932938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002752386,"about_ca_topic_score_gemma":6.628703e-7,"domain_scores_codex":[0.9993262,0.00005197695,0.0001538868,0.0002428095,0.0001164486,0.0001086222],"domain_scores_gemma":[0.9994639,0.00002992715,0.00006581437,0.0002711846,0.000106098,0.00006308134],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005146333,0.0001639408,0.00003904617,0.00003400741,0.00000922742,7.151623e-8,0.002199868,0.004390165,0.01942786,0.9023535,0.005392675,0.06598445],"study_design_scores_gemma":[0.0001938884,0.00008541676,0.00019003,0.000002138937,0.000001797347,0.000001943022,0.00001882867,0.9668302,0.01224201,0.0202041,0.0001332448,0.00009639689],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004790181,0.000005600132,0.9895424,0.000955659,0.00001356537,0.0006623763,4.873662e-7,0.0004375856,0.003592098],"genre_scores_gemma":[0.2497615,0.000001247227,0.749392,0.000312917,0.00001660378,0.00010334,0.00002329135,0.000005750546,0.000383352],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.96244,"threshold_uncertainty_score":0.4038101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03401756881031204,"score_gpt":0.2893119023646936,"score_spread":0.2552943335543815,"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."}}