{"id":"W2078724035","doi":"10.1109/infcom.2013.6567095","title":"Streaming codes for channels with burst and isolated erasures","year":2013,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Erasure; Upper and lower bounds; Channel (broadcasting); Algorithm; Block code; Code (set theory); Tornado code; Column (typography); Luby transform code; Concatenated error correction code; Online codes; Linear code; Decoding methods; Mathematics; Telecommunications; Set (abstract data type)","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":[0.0007025948,0.0004615533,0.0003436315,0.0004755224,0.0003493718,0.0005261019,0.0005120272,0.0005596277,0.0008802086],"category_scores_gemma":[0.004435669,0.0001492649,0.0002933759,0.0004686264,0.001194772,0.001063507,0.0007171186,0.0009205079,0.0001164767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000668668,"about_ca_system_score_gemma":0.0006392103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001057977,"about_ca_topic_score_gemma":0.0007774857,"domain_scores_codex":[0.9997057,0.00008965423,0.00001027082,0.00003258334,0.00009754137,0.00006422183],"domain_scores_gemma":[0.9971644,0.00193637,0.0003401992,0.0002044347,0.0002646069,0.00008995373],"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":[0.0001762108,0.00005472925,0.0009996084,0.0001305957,0.00002148629,0.0001805404,0.0001920235,0.4954927,0.02146377,0.4602835,0.0006758841,0.02032897],"study_design_scores_gemma":[0.00001895345,0.00006668486,0.000157448,0.00001514232,0.000008087154,0.00007556529,0.00003594299,0.9259285,0.006778534,0.0660614,0.0008400009,0.00001375078],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.388463,0.0006916014,0.6042098,0.000548624,0.00005155581,0.00008295273,0.0001115751,0.0001555755,0.005685346],"genre_scores_gemma":[0.9544854,0.000478289,0.04288571,0.00007880013,0.00005423462,0.00006741026,0.00006369579,0.00002193112,0.001864598],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001057977,"threshold_uncertainty_score":0.00485158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02935351133523197,"score_gpt":0.2591616130445689,"score_spread":0.2298081017093369,"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."}}