{"id":"W4386075276","doi":"10.1109/isit54713.2023.10206601","title":"Coded Downlink Massive Random Access","year":2023,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Overhead (engineering); Coding (social sciences); Computer science; Independent and identically distributed random variables; Telecommunications link; Information retrieval; Computer network; Theoretical computer science; Random variable; Mathematics; Statistics; Programming language","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":[0.000963238,0.001065447,0.001024961,0.0005921422,0.0007286071,0.001466671,0.00154264,0.001285346,0.004758631],"category_scores_gemma":[0.004098604,0.0003463109,0.0004198722,0.001319857,0.0009859214,0.001300506,0.002041904,0.001208588,0.001378823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001428794,"about_ca_system_score_gemma":0.0013719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005621092,"about_ca_topic_score_gemma":0.007250034,"domain_scores_codex":[0.9984728,0.0005126374,0.00003669922,0.0002460231,0.0003665143,0.0003653874],"domain_scores_gemma":[0.9977562,0.001071459,0.0002099815,0.0003986733,0.0004379601,0.0001258422],"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":[0.0005466653,0.0001469255,0.00153222,0.0003288273,0.00009883196,0.00154103,0.0001316469,0.7500879,0.006026441,0.1591543,0.01500349,0.06540172],"study_design_scores_gemma":[0.00006514975,0.00007349713,0.0002375149,0.00002002539,0.00002138119,0.0003583261,0.00002714585,0.9614894,0.0009292321,0.03238676,0.00436291,0.00002853019],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05191749,0.001852345,0.9034609,0.001607738,0.0006092921,0.0003000888,0.00160417,0.001811414,0.03683653],"genre_scores_gemma":[0.9359268,0.0008257535,0.04719393,0.0006487554,0.0002446383,0.0002443673,0.0007368172,0.00007038168,0.01410854],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005621092,"threshold_uncertainty_score":0.01591921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07683050920300423,"score_gpt":0.3399706379169419,"score_spread":0.2631401287139377,"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."}}