{"id":"W1984363480","doi":"10.1109/tcomm.2013.042313.120629","title":"Fourth-Order Statistics for Blind Classification of Spatial Multiplexing and Alamouti Space-Time Block Code Signals","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada; Memorial University of Newfoundland","funders":"","keywords":"Space–time block code; Block code; Algorithm; Fading; Spatial multiplexing; Nakagami distribution; Multiplexing; Computer science; Orthogonal frequency-division multiplexing; Antenna (radio); Electronic engineering; Channel (broadcasting); Telecommunications; MIMO; Decoding methods; 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":[0.0003310265,0.0001583975,0.0002070126,0.0002407322,0.0003946754,0.0001449867,0.0008555331,0.0001146306,0.00003218352],"category_scores_gemma":[0.00004198285,0.0001697237,0.00006270955,0.0003037378,0.0001894527,0.0004333397,0.00001581973,0.0002360921,0.00003173505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003771987,"about_ca_system_score_gemma":0.0001025712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002309794,"about_ca_topic_score_gemma":0.0002951061,"domain_scores_codex":[0.9986992,0.0002067071,0.0004532264,0.0002708672,0.0001924412,0.0001775905],"domain_scores_gemma":[0.9964488,0.001142044,0.0002422611,0.001490928,0.000588414,0.00008756147],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001851829,0.004807394,0.0001994876,0.0002288174,0.0006742062,6.908135e-7,0.01925273,0.06659792,0.4403114,0.1142401,0.008232567,0.3452695],"study_design_scores_gemma":[0.0006629036,0.0001619474,0.0005262442,0.00003284119,0.00003065504,0.000003726754,0.00007591177,0.9650154,0.02840279,0.00368518,0.001198172,0.0002042389],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00251234,0.00003160107,0.9911293,0.00453244,0.00005439144,0.001044861,0.0002002665,0.0002069658,0.0002877942],"genre_scores_gemma":[0.5783812,0.00007511611,0.4209163,0.00007274154,0.000005983357,0.0003080789,0.00001783933,0.00001335159,0.0002093959],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8984175,"threshold_uncertainty_score":0.6921132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05635321420031456,"score_gpt":0.3122429942863423,"score_spread":0.2558897800860278,"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."}}