{"id":"W2899037237","doi":"10.22215/etd/2018-13265","title":"Multilevel Polar Coded-Modulation for Wireless Communications","year":2018,"lang":"en","type":"dissertation","venue":"","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Forward error correction; MIMO; Fading; Algorithm; Hybrid automatic repeat request; Block code; Turbo code; Decoding methods; Electronic engineering; Theoretical computer science; Transmission (telecommunications); Telecommunications; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001288738,0.0002428118,0.0001851548,0.0003429448,0.0002631495,0.0006074726,0.0002193182,0.0003756781,0.00539942],"category_scores_gemma":[0.0004161585,0.00007825231,0.0000950368,0.0009272697,0.0002775074,0.0003798107,0.0003668883,0.000862422,0.001733768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004911117,"about_ca_system_score_gemma":0.000381439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004410299,"about_ca_topic_score_gemma":0.0006527639,"domain_scores_codex":[0.9998856,0.00001801381,0.000003746237,0.00001644552,0.0000645532,0.00001164142],"domain_scores_gemma":[0.999925,0.0000230118,0.000006336055,0.00001004527,0.00003105739,0.00000447617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007696402,0.00005180141,0.0002061897,0.0007270065,0.00001446282,0.0001215698,0.0003313679,0.005407149,0.04376538,0.3937899,0.02550444,0.5300038],"study_design_scores_gemma":[0.0000260675,0.0001413394,0.001185304,0.0005960109,0.00002306376,0.0006075382,0.0001642931,0.03266818,0.03096573,0.1993654,0.7342129,0.00004422955],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03186758,0.1813586,0.366978,0.006194691,0.002673368,0.0002335588,0.0006594871,0.0006436513,0.409391],"genre_scores_gemma":[0.520936,0.152569,0.1581046,0.001519147,0.001462009,0.0002749765,0.001025915,0.0001481452,0.1639602],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00539942,"threshold_uncertainty_score":0.01806283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04309928077665302,"score_gpt":0.3491862053461453,"score_spread":0.3060869245694922,"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."}}