{"id":"W3090535981","doi":"10.1145/3416010.3423217","title":"NeuRA","year":2020,"lang":"en","type":"article","venue":"","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Throughput; Sampling (signal processing); Frame (networking); Artificial neural network; Adaptation (eye); Variety (cybernetics); Sampling frame; Algorithm; Real-time computing; Machine learning; Artificial intelligence; Computer network; Wireless; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00002183105,0.00002717078,0.00003420264,0.000003549643,0.00001923098,0.0000641083,0.0003327919,0.00001026631,0.00006295209],"category_scores_gemma":[0.000003179766,0.00002075294,0.0000144619,0.0001262703,0.000003538982,0.0001178289,0.00009683485,0.00003346822,0.0001890474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001001972,"about_ca_system_score_gemma":0.00000742973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001568902,"about_ca_topic_score_gemma":1.996096e-7,"domain_scores_codex":[0.9997199,0.000008504636,0.00004291952,0.0001032524,0.00005359188,0.00007185133],"domain_scores_gemma":[0.9998016,0.00001153803,0.000008348789,0.0001095164,0.000007646003,0.00006139206],"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":[0.000002747023,0.00001038746,0.0005871759,0.000007705517,0.000003184346,0.00001931355,0.0002938012,0.0004123064,0.0003448825,0.6651889,0.09967492,0.2334546],"study_design_scores_gemma":[0.0001575022,0.00009303589,0.0008083274,0.00000244363,3.537038e-7,0.000002315112,0.000002519258,0.6091374,0.001508123,0.002523038,0.385658,0.0001069029],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0001975656,0.000007301618,0.9501886,0.01827027,0.00003970676,0.000517796,5.097994e-8,0.0002006623,0.03057809],"genre_scores_gemma":[0.9063603,0.00000187305,0.05737389,0.03520045,0.0003047791,0.0003055997,2.132999e-7,0.000004740113,0.0004481142],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9061628,"threshold_uncertainty_score":0.2429885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03294977198091718,"score_gpt":0.229913104052632,"score_spread":0.1969633320717148,"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."}}