{"id":"W3141340642","doi":"10.34117/bjdv7n3-452","title":"EFEITO DA INTERFERÊNCIA EPIDÊMICA NA PROBABILIDADE DE ERRO DE UM SISTEMA CELULAR / EFFECT OF EPIDEMIC INTERFERENCE ON THE PROBABILITY OF ERROR IN A CELLULAR SYSTEM","year":2021,"lang":"pt","type":"article","venue":"Brazilian Journal of Development","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Interference (communication); Probability of error; Physics; Statistics; Mathematics; Computer science; Algorithm; Telecommunications","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.006150166,0.0004622704,0.001318494,0.0003080627,0.00008521359,0.00004310812,0.001318352,0.0002330949,0.0000523986],"category_scores_gemma":[0.001621966,0.0003565395,0.00040268,0.0006482216,0.0001499009,0.0001235302,0.0003414605,0.001089551,0.000009764289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001703502,"about_ca_system_score_gemma":0.001542861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001615143,"about_ca_topic_score_gemma":0.00007429826,"domain_scores_codex":[0.9937414,0.002112741,0.002804913,0.000321332,0.0004527535,0.0005668678],"domain_scores_gemma":[0.9958228,0.001344943,0.001061267,0.001105188,0.0004254836,0.0002403071],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003218953,0.003738073,0.2057678,0.04867672,0.003238641,0.0008156036,0.05284766,0.04191371,0.6125952,0.002529908,0.001292718,0.02336508],"study_design_scores_gemma":[0.002275219,0.001104254,0.04651268,0.03010007,0.000284682,0.0003666707,0.002179817,0.008549637,0.9069345,0.0001805867,0.0007978036,0.0007140677],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990429,0.002552033,0.004943631,0.0006114772,0.0003863097,0.0006956503,0.00001348657,0.00001804253,0.0003503059],"genre_scores_gemma":[0.9929236,0.0000645688,0.006769746,0.0000276937,0.00003802444,0.00004831037,0.000004971713,0.00004787228,0.00007526146],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2943393,"threshold_uncertainty_score":0.9998887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03076249981995696,"score_gpt":0.2679520854294417,"score_spread":0.2371895856094847,"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."}}