{"id":"W2004733292","doi":"10.1109/tvt.2011.2119337","title":"Correction to \"Downlink Scheduling via Genetic Algorithms for Multiuser Single-Carrier and Multicarrier MIMO Systems With Dirty Paper Coding\" [Sep 09 3247-3262]","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Telecommunications link; Coding (social sciences); Computer science; Scheduling (production processes); Algorithm; Error detection and correction; Electronic engineering; Telecommunications; Mathematics; Engineering; Mathematical optimization; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005217406,0.003638599,0.002127292,0.003245231,0.002747246,0.002386682,0.00561158,0.006851885,0.05472065],"category_scores_gemma":[0.06534808,0.001406873,0.002286904,0.003891577,0.002793286,0.00313303,0.00343127,0.01070396,0.03022275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005128009,"about_ca_system_score_gemma":0.0057131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02695128,"about_ca_topic_score_gemma":0.01751961,"domain_scores_codex":[0.9927762,0.001749919,0.0008290683,0.000801723,0.003403233,0.0004399192],"domain_scores_gemma":[0.9623943,0.009274621,0.001809425,0.003773538,0.02219202,0.0005561149],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001214807,0.00002971475,0.0001522072,0.000328904,0.00005236676,0.0002527633,0.0001544307,0.001353552,0.0004211555,0.01204187,0.9678046,0.01728694],"study_design_scores_gemma":[0.000170021,0.00007565648,0.001315563,0.0005583556,0.0001174308,0.0006715903,0.0001367655,0.0229527,0.004322896,0.01588432,0.9535807,0.0002139559],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.001294871,0.003300664,0.07202322,0.08775187,0.8144314,0.0001914676,0.00406313,0.007524884,0.009418502],"genre_scores_gemma":[0.08779338,0.01275365,0.1895581,0.1261666,0.1489755,0.001249912,0.00965309,0.007068425,0.4167813],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05472065,"threshold_uncertainty_score":0.1830588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01525316776681777,"score_gpt":0.2123862989698144,"score_spread":0.1971331312029966,"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."}}