{"id":"W4362598856","doi":"10.48550/arxiv.2304.01005","title":"Federated Learning Based Multilingual Emoji Prediction In Clean and Attack Scenarios","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Internet Traffic Analysis and Secure E-voting","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Queen's University","keywords":"Emoji; Computer science; Transformer; Training set; Artificial intelligence; Machine learning; Federated learning; Ensemble learning; Social media; World Wide Web","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005068243,0.0002776659,0.0003443372,0.0004583047,0.0002056643,0.0002540164,0.000555998,0.0002990016,0.000016073],"category_scores_gemma":[0.00009267023,0.0003262449,0.000145504,0.0006268473,0.00006232534,0.0002118822,0.0008533179,0.001013381,0.00005218071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001696567,"about_ca_system_score_gemma":0.0001383167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002229569,"about_ca_topic_score_gemma":0.001132786,"domain_scores_codex":[0.9978645,0.0002401547,0.0002883155,0.001145642,0.0001117041,0.0003497128],"domain_scores_gemma":[0.9991691,0.0001409473,0.0002120193,0.0002335752,0.0001302314,0.0001141252],"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":[0.00001885063,0.00004318025,0.007667821,0.00004428815,0.00004990061,0.0003059176,0.0005477467,0.9878752,0.00000506456,0.002173575,0.00007115475,0.001197261],"study_design_scores_gemma":[0.0005190338,0.00004804765,0.003524757,0.0001975953,0.00003369102,0.000001724392,0.0003523936,0.9949304,0.00002059066,0.00003246248,0.00006473625,0.0002745645],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6222249,0.00001038249,0.376927,0.00003935821,0.0002510618,0.0001215876,0.000002781361,0.0003061548,0.0001167973],"genre_scores_gemma":[0.9978722,0.00002236614,0.0003431364,0.00004069962,0.00006170372,5.639632e-7,0.00003639744,0.00002173517,0.001601191],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3765839,"threshold_uncertainty_score":0.9999189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07068250201920404,"score_gpt":0.2125931844779169,"score_spread":0.1419106824587128,"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."}}