{"id":"W2027249873","doi":"10.1155/2013/578710","title":"Discrete Artificial Bee Colony for Computationally Efficient Symbol Detection in Multidevice STBC MIMO Systems","year":2013,"lang":"en","type":"article","venue":"Advances in Artificial Intelligence","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Algorithm; Space–time block code; Computer science; MIMO; Artificial bee colony algorithm; Decoding methods; Block (permutation group theory); Minimum mean square error; Mathematical optimization; Block code; Mathematics; Statistics; Artificial intelligence; Estimator; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004484185,0.0002025894,0.0002443935,0.0002489184,0.0002362465,0.0001929094,0.0006386732,0.00008729738,0.000009130038],"category_scores_gemma":[0.0001451446,0.0002091429,0.00006851598,0.0009947035,0.0001261373,0.0008435762,0.0001091721,0.0001938283,0.0001629626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001784683,"about_ca_system_score_gemma":0.00007112144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000424134,"about_ca_topic_score_gemma":0.00104179,"domain_scores_codex":[0.9976506,0.00009212637,0.0008525645,0.0006496695,0.0003087656,0.0004462356],"domain_scores_gemma":[0.9984856,0.0006618478,0.0002034152,0.0002889395,0.0002709256,0.0000892662],"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":[0.00001592662,0.0002373196,0.00008063448,0.00003142974,0.000003739784,0.000002149174,0.0004387896,0.6482201,0.003098766,0.1914292,0.00001284874,0.1564292],"study_design_scores_gemma":[0.00004734693,0.00008602348,0.0007984077,0.00005790524,0.000002468024,0.000004230007,0.0005088726,0.9284833,0.005666137,0.06328816,0.0008177128,0.0002394345],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03794655,0.0006286149,0.9581057,0.0008321306,0.0007093514,0.001545658,0.00001386689,0.00009488377,0.0001231975],"genre_scores_gemma":[0.9633543,0.0000473192,0.03510135,0.00007456169,0.0001527945,0.001221956,0.000010165,0.0000129336,0.00002464787],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9254077,"threshold_uncertainty_score":0.8528601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02296798730928299,"score_gpt":0.3076158358688979,"score_spread":0.2846478485596149,"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."}}