{"id":"W2371171758","doi":"","title":"Research on encode and decode of LDPC used to CMMB system and its performance analyses","year":2009,"lang":"en","type":"article","venue":"Application of Electronic Technique","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"L'Alliance Boviteq","funders":"","keywords":"Computer science; Low-density parity-check code; Coding (social sciences); Decoding methods; Algorithm; Code (set theory); MATLAB; ENCODE; Orthogonal frequency-division multiplexing; Encoding (memory); Computer hardware; Computer engineering; Telecommunications; Mathematics; Artificial intelligence","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":[0.0003017912,0.0004980402,0.0003496752,0.0008052284,0.0003842587,0.000488264,0.0002967694,0.0005116608,0.002292457],"category_scores_gemma":[0.002090243,0.0001622829,0.0001961793,0.0008708141,0.0003647408,0.0008572437,0.0002342941,0.0004131329,0.0004173872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007226673,"about_ca_system_score_gemma":0.0006765772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003537698,"about_ca_topic_score_gemma":0.00273957,"domain_scores_codex":[0.9995385,0.0001124652,0.00001469017,0.0000579279,0.0002308769,0.00004550326],"domain_scores_gemma":[0.9992969,0.0003414395,0.00005373719,0.00005785813,0.0002349256,0.00001517726],"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":[0.0005942353,0.0001111306,0.00527599,0.0007229043,0.0001217398,0.00068082,0.0008182979,0.2688323,0.1495766,0.2099252,0.004247325,0.3590934],"study_design_scores_gemma":[0.00002999583,0.0002042903,0.001257524,0.00006186865,0.00004517467,0.0006524684,0.00007732003,0.9016692,0.07765582,0.01077263,0.007536886,0.00003677322],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1562757,0.005467831,0.808962,0.0005882703,0.0001098354,0.00009897713,0.0001354011,0.0007692907,0.02759262],"genre_scores_gemma":[0.8781458,0.003869518,0.1086005,0.0001217279,0.00008674995,0.00009484411,0.0001768187,0.00007098383,0.00883296],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003537698,"threshold_uncertainty_score":0.007669032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05939878122197263,"score_gpt":0.4037883663613553,"score_spread":0.3443895851393827,"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."}}