{"id":"W7000409524","doi":"","title":"Federated learning algorithms on top of distributed relational database systems","year":2020,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fonds de recherche du Québec – Nature et technologies; McGill University","keywords":"Relational database; Distributed database; Relational model; Relational algebra; Feature (linguistics); Database theory","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005020033,0.0007280497,0.002200126,0.001733863,0.001508121,0.004536991,0.004716551,0.001265647,0.005220646],"category_scores_gemma":[0.01907463,0.001002008,0.001296317,0.00260363,0.001361047,0.007657377,0.003779158,0.003163882,0.001672351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002122736,"about_ca_system_score_gemma":0.002569514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006795926,"about_ca_topic_score_gemma":0.005512541,"domain_scores_codex":[0.9943426,0.00192063,0.0005561897,0.0009180689,0.001732705,0.000529797],"domain_scores_gemma":[0.9855568,0.005960611,0.0003503741,0.005668677,0.001990965,0.0004726464],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001659765,0.0005921792,0.002427762,0.0002100178,0.0003002283,0.0002134798,0.0003842125,0.3101372,0.004744654,0.1272468,0.01699794,0.5350859],"study_design_scores_gemma":[0.00009148887,0.00007103308,0.0002692528,0.00002637157,0.00003499034,0.00006203153,0.00005726134,0.8771508,0.003763617,0.1140258,0.004430818,0.00001651916],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02839228,0.0007532156,0.9607907,0.0006282001,0.0001883043,0.00009905059,0.0002259082,0.005795339,0.003127025],"genre_scores_gemma":[0.3907341,0.0004798855,0.601022,0.0002537766,0.0001796714,0.0001779732,0.0007969757,0.0004205209,0.005935039],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006795926,"threshold_uncertainty_score":0.0265488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03479440469322503,"score_gpt":0.264451812357435,"score_spread":0.22965740766421,"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."}}