{"id":"W2889636654","doi":"10.1109/icassp.2018.8462276","title":"Digital-Analog Superposition Coding for Ofdm Channels with Application To Video Transmission","year":2018,"lang":"en","type":"article","venue":"","topic":"Video Coding and Compression Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Orthogonal frequency-division multiplexing; Computer science; Quadrature amplitude modulation; Analog transmission; Encoder; Quantization (signal processing); Electronic engineering; QAM; Video quality; Multiplexing; Coding (social sciences); Transmission (telecommunications); Bit error rate; Analog signal; Algorithm; Telecommunications; Decoding methods; Mathematics; Channel (broadcasting); Engineering","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":[0.0001018158,0.0001127935,0.0001170251,0.0001333168,0.0002252335,0.0002553365,0.0005945739,0.00005940793,0.000005618056],"category_scores_gemma":[0.00002181891,0.00007934968,0.00003717075,0.0003720707,0.00003757048,0.0004782388,0.00009548329,0.00004476716,0.00004470794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002323157,"about_ca_system_score_gemma":0.00001809382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005062836,"about_ca_topic_score_gemma":0.000001812038,"domain_scores_codex":[0.9990731,0.00000753603,0.0001434195,0.0003967445,0.0001669249,0.0002123039],"domain_scores_gemma":[0.9992487,0.00006559797,0.00003753766,0.0004227456,0.0001486775,0.00007675704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005131786,0.00005342607,0.00007286889,0.00001769391,0.00001194588,6.575784e-7,0.0003339644,0.00009255834,0.02946207,0.05214982,0.00479828,0.9129554],"study_design_scores_gemma":[0.000758704,0.002011688,0.0002289123,0.0002055345,0.0000141945,0.00002382357,0.0001450119,0.2520463,0.6398945,0.03187113,0.0722246,0.0005755059],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00506937,0.00001131174,0.9871109,0.003907729,0.00006523848,0.0003933634,0.000001870942,0.0007760625,0.002664181],"genre_scores_gemma":[0.917845,0.000002555361,0.08092226,0.000370327,0.00005545549,0.0001550351,0.000003073275,0.000007693353,0.0006385838],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9127756,"threshold_uncertainty_score":0.3235786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01580794778397651,"score_gpt":0.2524582308773147,"score_spread":0.2366502830933382,"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."}}