{"id":"W4401692380","doi":"10.1109/isit57864.2024.10619539","title":"Subset Adaptive Relaying for Streaming Erasure Codes","year":2024,"lang":"en","type":"article","venue":"","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Erasure; Erasure code; Online codes; Computer network; Decoding methods; Algorithm; Block code; Programming language; Concatenated error correction code","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":[0.0001944071,0.00007665379,0.00007822709,0.00006181485,0.0000976953,0.0002743969,0.0002519763,0.0000306065,0.00000515403],"category_scores_gemma":[0.00001818757,0.00006233156,0.00007902025,0.0001360805,0.000009924446,0.0003341508,0.00006705087,0.00008479491,0.00003011652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002722807,"about_ca_system_score_gemma":0.00003923511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007041236,"about_ca_topic_score_gemma":0.00002899326,"domain_scores_codex":[0.9993523,0.00001618705,0.00009346718,0.0002687263,0.0001095266,0.0001598379],"domain_scores_gemma":[0.9995186,0.0002185038,0.00001131559,0.0001804095,0.00003461941,0.00003657547],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001383136,0.00002603482,0.0002601781,0.00004868897,0.00009532474,0.00005352146,0.00112166,0.0003066597,0.005128495,0.7383178,0.01740383,0.237224],"study_design_scores_gemma":[0.0001393492,0.00009917242,0.0001510961,0.0001113741,0.00001264342,0.00001874871,0.0002110247,0.9870971,0.001103871,0.004898283,0.005970683,0.0001866441],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02315786,0.0008821433,0.9698325,0.0007235349,0.0006185798,0.0001053184,0.000008558922,0.0005342352,0.004137206],"genre_scores_gemma":[0.9847872,0.000008998557,0.01193204,0.0001764059,0.00007547728,0.00001502766,0.000002587585,0.000006714651,0.002995532],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9867905,"threshold_uncertainty_score":0.2646016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03234283740478306,"score_gpt":0.2541689741761917,"score_spread":0.2218261367714087,"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."}}