{"id":"W2489997503","doi":"10.1109/tbc.2016.2590824","title":"Multiple Service Configurations Based on Layered Division Multiplexing","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Broadcasting","topic":"Telecommunications and Broadcasting Technologies","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Communications Research Centre Canada","funders":"Ministry of Science, ICT and Future Planning","keywords":"Multiplexing; Computer science; Division (mathematics); Telecommunications; Time-division multiplexing; Service (business); Frequency-division multiplexing; Electronic engineering; Orthogonal frequency-division multiplexing; Computer network; Electrical engineering; Engineering; Business; Mathematics; Channel (broadcasting)","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":[0.0001469801,0.0002869699,0.0002063129,0.0003422466,0.0005009471,0.0000640613,0.0003717523,0.0001661602,0.0001186486],"category_scores_gemma":[0.00009395647,0.0002324213,0.0001039791,0.0005967708,0.00005546119,0.0002084824,0.000003351367,0.0003596103,0.0001989198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001485186,"about_ca_system_score_gemma":0.00002325675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003453684,"about_ca_topic_score_gemma":0.00009909004,"domain_scores_codex":[0.9986501,0.00004975052,0.0003769487,0.0003081993,0.0002184024,0.0003966446],"domain_scores_gemma":[0.9978103,0.001178853,0.00006563865,0.0007546828,0.0001068885,0.0000836261],"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":[0.00001686744,0.00009311976,0.00005640151,0.00002622918,0.00002053616,0.000001978742,0.00006821125,0.6768195,0.1040514,0.00001914373,0.0000848644,0.2187417],"study_design_scores_gemma":[0.001125193,0.0001010066,0.0005992732,0.0004876483,0.00001142429,0.000005269921,0.0001068574,0.8585818,0.136694,0.00003403472,0.001861002,0.0003924682],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06796471,0.00002246816,0.9264421,0.0007440849,0.0003829202,0.0002553912,0.000118692,0.002632332,0.001437338],"genre_scores_gemma":[0.9859778,0.00002176789,0.01359143,0.0001184583,0.00002953074,0.0001103478,0.000006383757,0.00006888564,0.00007534453],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9180132,"threshold_uncertainty_score":0.9477867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02880485097279815,"score_gpt":0.2288523350491859,"score_spread":0.2000474840763877,"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."}}