{"id":"W4402980560","doi":"10.1109/icme57554.2024.10688130","title":"The Prospect of Enhancing Large-Scale Heterogeneous Federated Learning with Foundation Models","year":2024,"lang":"en","type":"article","venue":"","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Research Foundation Singapore","keywords":"Foundation (evidence); Computer science; Scale (ratio)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005326558,0.0007394715,0.0008190805,0.000585938,0.0005544176,0.001838534,0.00224357,0.001086569,0.00156362],"category_scores_gemma":[0.0106558,0.0003101699,0.0006787362,0.0009473888,0.00134004,0.007783913,0.003130348,0.002183211,0.000493036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001131556,"about_ca_system_score_gemma":0.0015434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002100022,"about_ca_topic_score_gemma":0.002917096,"domain_scores_codex":[0.9984331,0.0006339563,0.00007354585,0.0004053205,0.0002741244,0.0001799431],"domain_scores_gemma":[0.9931719,0.001809951,0.0004082767,0.003759866,0.0005781405,0.0002719424],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006830471,0.0009576927,0.008528283,0.0001994682,0.000278165,0.0002814415,0.0003691306,0.5276921,0.01222646,0.07118753,0.007794333,0.3698022],"study_design_scores_gemma":[0.00002014432,0.00009389997,0.0003104504,0.00001132836,0.00001795265,0.0000665474,0.00007886092,0.9549711,0.004755852,0.03782767,0.001836811,0.000009435514],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06238452,0.000253996,0.931726,0.001073535,0.00004832153,0.00008382874,0.00009992318,0.002337185,0.001992667],"genre_scores_gemma":[0.8315153,0.0002030109,0.1659027,0.0004859306,0.00003879903,0.00007220843,0.0002898653,0.0001097125,0.001382443],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005326558,"threshold_uncertainty_score":0.02816987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01740031785767957,"score_gpt":0.2550279524936474,"score_spread":0.2376276346359678,"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."}}