{"id":"W2101173152","doi":"10.1109/glocom.2005.1577915","title":"A variational free energy minimization interpretation of multiuser detection in CDMA","year":2005,"lang":"en","type":"article","venue":"GLOBECOM '05. IEEE Global Telecommunications Conference, 2005.","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Multiuser detection; Maximization; Computer science; Detector; Decoding methods; Minification; Heuristic; Energy (signal processing); Mathematical optimization; Algorithm; Code division multiple access; Mathematics; Artificial intelligence; Telecommunications; Statistics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000684146,0.0003412745,0.0004392558,0.0005402499,0.0003006988,0.0002541554,0.00533151,0.0002967647,0.000123107],"category_scores_gemma":[0.0002926008,0.0003920622,0.0001488668,0.002045528,0.0002171455,0.001501818,0.001068835,0.0004593243,0.00006420497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007948069,"about_ca_system_score_gemma":0.0005876424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001115289,"about_ca_topic_score_gemma":0.01772892,"domain_scores_codex":[0.9958906,0.0009673818,0.001256562,0.0005850054,0.0006804271,0.0006200155],"domain_scores_gemma":[0.9942462,0.0004772502,0.0005860837,0.003644568,0.000852577,0.0001933205],"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":[0.0001107369,0.00142282,0.001699689,0.00002786789,0.0001255451,0.000002159991,0.0009726551,0.0860056,0.0008548144,0.2049051,0.008275837,0.6955972],"study_design_scores_gemma":[0.001220948,0.00006917126,0.01063152,0.00008249935,0.00001236705,0.00002169141,0.00006297533,0.966395,0.001049013,0.005867576,0.0142261,0.0003611547],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008518798,0.0005138706,0.9720723,0.00600854,0.0003343787,0.000504284,0.00007689695,0.0002689754,0.01170195],"genre_scores_gemma":[0.8744203,0.0007695952,0.1239618,0.0002683403,0.00006378433,0.000202696,0.0001201425,0.00001746604,0.0001759203],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8803894,"threshold_uncertainty_score":0.9998531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02150182340802422,"score_gpt":0.2814710991454904,"score_spread":0.2599692757374662,"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."}}