{"id":"W4406983186","doi":"10.1109/tsc.2025.3536320","title":"DeFedGCN: Privacy-Preserving Decentralized Federated GCN for Recommender System","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Services Computing","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Computer science; Recommender system; Information privacy; Computer security; Internet privacy; World Wide Web","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"],"consensus_categories":[],"category_scores_codex":[0.0006011497,0.0003467569,0.0004617947,0.0003530358,0.0009645976,0.0007500129,0.001531826,0.0001795438,0.000006818555],"category_scores_gemma":[0.000003287571,0.0003412676,0.0002437909,0.0008183662,0.00001388061,0.0004925676,0.00003794115,0.0002792551,0.00001361123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002298335,"about_ca_system_score_gemma":0.00008125989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002679099,"about_ca_topic_score_gemma":0.0001116543,"domain_scores_codex":[0.9975045,0.0002122227,0.0007138267,0.0007475324,0.0002318803,0.0005900432],"domain_scores_gemma":[0.9980894,0.0004631954,0.0002298463,0.0008555757,0.0002434753,0.0001185157],"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":[0.0004414779,0.001766071,0.0007737912,0.0129059,0.00243946,0.00004810769,0.01004305,0.03432705,0.006119261,0.05774893,0.01434538,0.8590415],"study_design_scores_gemma":[0.001257607,0.00009156008,0.00006232379,0.001236824,0.00004255935,0.00002110677,0.0005420439,0.9627956,0.02152358,0.0006907561,0.01130645,0.0004296212],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004476142,0.0001309536,0.9866519,0.001342183,0.002408152,0.0009530677,0.000008331855,0.001703185,0.002326103],"genre_scores_gemma":[0.9140447,0.00001521513,0.08464684,0.0009606708,0.0000476227,0.00008197522,0.000004084338,0.0000280032,0.0001708633],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9284685,"threshold_uncertainty_score":0.9999039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01909109743749904,"score_gpt":0.2816092261796781,"score_spread":0.2625181287421791,"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."}}