{"id":"W2140468967","doi":"10.1109/ccece.2011.6030586","title":"Adaptive modulation for OFDM system with varying speed receiver","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Orthogonal frequency-division multiplexing; Fading; Link adaptation; Channel (broadcasting); Electronic engineering; Modulation (music); Bit error rate; Signal-to-noise ratio (imaging); Noise (video); Control theory (sociology); Telecommunications; Engineering; Acoustics; Physics","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":[0.00003204604,0.00009225613,0.00009434753,0.00003930606,0.00003525821,0.000005795308,0.0000401068,0.00004130164,0.0000200183],"category_scores_gemma":[0.000002045997,0.00008078113,0.00001622263,0.0001074951,0.000007981857,0.0002217545,0.000004747762,0.00003500518,0.000008575547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007772542,"about_ca_system_score_gemma":0.000003559257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007852825,"about_ca_topic_score_gemma":0.000005069362,"domain_scores_codex":[0.9995888,0.000005320648,0.0001057427,0.0001091372,0.00005848487,0.0001325405],"domain_scores_gemma":[0.9997643,0.00001972987,0.00002582246,0.0001020047,0.00005935274,0.0000287406],"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":[0.00004914622,0.000003508912,0.00006897061,0.00003156968,0.00002249078,6.505316e-7,0.0001942479,0.9941691,0.000186498,0.002966496,0.00005245002,0.002254882],"study_design_scores_gemma":[0.0003156601,0.00003976176,0.0002793041,0.00004726733,0.00001009164,0.000002226012,0.00009132748,0.9969649,0.002042694,0.00006614593,0.00001852081,0.0001221465],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004601469,0.00001646027,0.9642218,0.000001312058,0.0001070377,0.0003276074,0.00000209098,0.0005157357,0.03020644],"genre_scores_gemma":[0.8104847,0.00000357437,0.189277,0.000003702167,0.0000464736,0.00001846658,0.000009864764,0.00003319674,0.0001229879],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8058832,"threshold_uncertainty_score":0.3294159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02498294164049096,"score_gpt":0.1896450265732544,"score_spread":0.1646620849327635,"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."}}