{"id":"W3086990738","doi":"10.1109/lcomm.2020.3023074","title":"Reliable Broadcast Based on Online Fountain Codes","year":2020,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Glycemic Index Laboratories; University of Alberta","funders":"Natural Science Foundation of Beijing Municipality; China Scholarship Council; National Natural Science Foundation of China","keywords":"Fountain code; Computer science; Fountain; Decoding methods; Raptor code; Luby transform code; Scheme (mathematics); Code (set theory); Wireless; Theoretical computer science; Algorithm; Computer network; Telecommunications; Block code; Concatenated error correction code; Mathematics","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":[0.0008349061,0.0005051729,0.0006030817,0.0007145379,0.0005236664,0.0007510068,0.0008830291,0.0009028534,0.0008971727],"category_scores_gemma":[0.004988329,0.0002085068,0.0003416722,0.0007859157,0.001330244,0.001551689,0.0007931953,0.0009083607,0.0002193069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001214804,"about_ca_system_score_gemma":0.0007445052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003789502,"about_ca_topic_score_gemma":0.002082296,"domain_scores_codex":[0.9990174,0.0002842344,0.00002841031,0.00009423695,0.0003753179,0.000200465],"domain_scores_gemma":[0.9967,0.001817279,0.0004508352,0.0004263214,0.0005276803,0.00007789863],"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":[0.0005345464,0.00007581755,0.001473872,0.0002252284,0.00007999106,0.0005075544,0.000657982,0.6801236,0.03521673,0.2268602,0.001715672,0.05252881],"study_design_scores_gemma":[0.00001739072,0.00006979725,0.0001528212,0.00001324407,0.00001216599,0.0001262931,0.00003506518,0.9770921,0.00447057,0.01712582,0.0008643285,0.00002048584],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1198798,0.001153994,0.873009,0.0002726242,0.00007921471,0.00005241938,0.00005434947,0.0002953266,0.005203264],"genre_scores_gemma":[0.9675398,0.0003711858,0.0298927,0.0000610835,0.00004489747,0.00003962966,0.00002446622,0.00002537982,0.002000906],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003789502,"threshold_uncertainty_score":0.008814037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.062511879357247,"score_gpt":0.3026936390537778,"score_spread":0.2401817596965308,"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."}}