{"id":"W3201304585","doi":"10.48550/arxiv.2109.05662","title":"Training Fair Models in Federated Learning without Data Privacy Infringement","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Huawei Technologies (Canada)","funders":"","keywords":"Silo; Training (meteorology); Computer science; Cross country; Geography; Economics; Archaeology; Demographic economics","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","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0009533226,0.0005000839,0.0006183984,0.0005732263,0.0002441807,0.0007006985,0.05289721,0.0005012054,0.00001799039],"category_scores_gemma":[0.004548173,0.0006387562,0.00009698034,0.001342092,0.0001346384,0.002547677,0.4137548,0.002210275,0.00001697284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004955446,"about_ca_system_score_gemma":0.0006244004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003798594,"about_ca_topic_score_gemma":0.0002058114,"domain_scores_codex":[0.9953951,0.0003388475,0.0004313076,0.002860537,0.0002295523,0.0007446544],"domain_scores_gemma":[0.9832837,0.0001593477,0.0003948058,0.01587333,0.0001527168,0.0001361317],"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":[0.00004299055,0.0003003626,0.01265368,0.0002893629,0.0003635396,0.00279656,0.001784492,0.9452415,0.0001484187,0.01647046,0.003277144,0.01663145],"study_design_scores_gemma":[0.0004782005,0.00002335966,0.0004451193,0.0003795773,0.000025444,0.000006457918,0.0005373056,0.9058084,0.00007081784,0.09129532,0.0003427625,0.000587185],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2277365,0.00011254,0.7675627,0.0008354487,0.0003437136,0.0003343433,0.00002079097,0.001197918,0.001855951],"genre_scores_gemma":[0.9154686,0.0004029764,0.08359195,0.0000590397,0.00002791464,0.000002569478,0.0002647417,0.00003374537,0.0001484359],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6877321,"threshold_uncertainty_score":0.9996064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2430394936791592,"score_gpt":0.2500535423072757,"score_spread":0.007014048628116554,"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."}}