{"id":"W4403919398","doi":"10.1109/tifs.2024.3488500","title":"Eyes on Federated Recommendation: Targeted Poisoning With Competition and Its Mitigation","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Information Forensics and Security","topic":"Pharmacology and Obesity Treatment","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Computer science; Competition (biology); Computer security","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":[],"consensus_categories":[],"category_scores_codex":[0.00008537537,0.0001169924,0.0001174082,0.0001491453,0.0003000819,0.00008246928,0.000009522243,0.00007840002,0.0001022342],"category_scores_gemma":[0.000002370346,0.00009407254,0.00002517116,0.0001376002,0.0000395169,0.0005558091,5.632218e-7,0.0002217986,0.0000279072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005874346,"about_ca_system_score_gemma":0.00003700097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007382432,"about_ca_topic_score_gemma":0.0000139147,"domain_scores_codex":[0.9994955,0.00002231563,0.0001687607,0.0001106125,0.0001054039,0.00009739938],"domain_scores_gemma":[0.9996971,0.00005585756,0.00003600919,0.00003857165,0.00009353961,0.00007891411],"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":[0.01149502,0.002265679,0.001199918,0.005016111,0.00402069,0.0001773737,0.05084926,0.005783111,0.005543074,0.1377213,0.007790606,0.7681379],"study_design_scores_gemma":[0.01396669,0.007592437,0.01109334,0.002067133,0.001378768,0.0009040964,0.002931806,0.6614122,0.2619117,0.00507262,0.03045032,0.001218873],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9380311,0.0000826137,0.05462823,0.004107714,0.0003650817,0.0004866688,0.0001260227,0.000190936,0.001981632],"genre_scores_gemma":[0.9983636,0.0002228482,0.0001766962,0.0009058876,0.00002074255,0.00002610522,0.0002410526,0.000005742148,0.00003738754],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.766919,"threshold_uncertainty_score":0.3836167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009486922414118616,"score_gpt":0.2565432482598259,"score_spread":0.2470563258457073,"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."}}