{"id":"W4387007046","doi":"10.1145/3603165.3607364","title":"Plato: An Open-Source Research Framework for Production Federated Learning","year":2023,"lang":"en","type":"article","venue":"","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Testbed; Emulation; Scalability; Server; Implementation; Variety (cybernetics); Cloud computing; Open source; Artificial intelligence; Open research; Key (lock); Deep learning; Data science; World Wide Web; Software engineering; Operating system; Software","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":["metaresearch","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.003962948,0.0001145915,0.0001385069,0.0003068003,0.001026246,0.001307121,0.03029592,0.0001872858,0.00001846753],"category_scores_gemma":[0.1021458,0.0001066159,0.0000179345,0.002654946,0.0001196626,0.001590205,0.1077941,0.0007529063,0.0002349848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007190319,"about_ca_system_score_gemma":0.00009157799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008612587,"about_ca_topic_score_gemma":0.00002482792,"domain_scores_codex":[0.9975897,0.0002160956,0.0002119394,0.0009247243,0.000433765,0.0006237887],"domain_scores_gemma":[0.993203,0.0007404428,0.00005811786,0.005652008,0.0002717588,0.00007467002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002820657,0.00008079324,0.0005218927,0.00002898777,0.00002017718,0.000007693249,0.0003022937,0.0004263687,0.002843909,0.07625282,0.7875683,0.1319185],"study_design_scores_gemma":[0.0001169247,0.0002343468,0.0002157424,0.00003927592,8.50658e-7,0.000005310814,0.0004286752,0.3866746,0.01237436,0.5624986,0.03724872,0.0001626763],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0395175,0.00001434339,0.8881585,0.06462827,0.0004590318,0.0008054995,0.000001861079,0.005524336,0.0008906636],"genre_scores_gemma":[0.1674778,0.00002573999,0.828634,0.00009305093,0.0001245172,0.0002304721,0.00003914112,0.00003287462,0.003342377],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7503196,"threshold_uncertainty_score":0.9997296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1869034082109738,"score_gpt":0.4195990269202635,"score_spread":0.2326956187092897,"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."}}