{"id":"W2562227685","doi":"10.1007/978-3-319-51204-4_13","title":"Towards Dynamic Wireless Capacity Management for the Masses","year":2016,"lang":"en","type":"book-chapter","venue":"Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Wireless; Cloud computing; Spectrum management; Computer network; Protocol (science); Architecture; The Internet; Physical layer; Distributed computing; Cognitive radio; Telecommunications","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":[0.001132091,0.0009980543,0.0008994344,0.0005668311,0.0005861626,0.003250513,0.00201018,0.001076565,0.006557356],"category_scores_gemma":[0.003323726,0.0004587013,0.0003433542,0.0009488265,0.001384913,0.004969733,0.002830647,0.002671259,0.00145194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001217075,"about_ca_system_score_gemma":0.0008249529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001164557,"about_ca_topic_score_gemma":0.001035618,"domain_scores_codex":[0.9995196,0.0001226596,0.00001436765,0.000109517,0.0001386341,0.00009509534],"domain_scores_gemma":[0.999099,0.0004371805,0.00009385656,0.0001500582,0.0001412316,0.00007869286],"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":[0.00008782444,0.00008674274,0.0002176082,0.0001533711,0.0000512749,0.0001113066,0.0002687294,0.3983253,0.006541701,0.430634,0.01406261,0.1494594],"study_design_scores_gemma":[0.00001048886,0.00003183116,0.00009332113,0.00003737032,0.00001258613,0.00005095584,0.0000656541,0.5935062,0.001496434,0.3909727,0.0137036,0.00001893374],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01317501,0.002834623,0.9539243,0.002137669,0.0002831234,0.000030989,0.0001188403,0.0005011665,0.02699426],"genre_scores_gemma":[0.8295315,0.004864913,0.132657,0.0006071841,0.001368455,0.0001621963,0.0001907124,0.0003416132,0.03027651],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006557356,"threshold_uncertainty_score":0.02193648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01867704201627357,"score_gpt":0.2304637265746685,"score_spread":0.2117866845583949,"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."}}