{"id":"W4412367173","doi":"10.1109/tbc.2025.3583989","title":"Novel Distributed Multimedia Recommendation Systems Using Personalized Information","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Broadcasting","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Science and Technology Council; National Natural Science Foundation of China; National Science Foundation","keywords":"Computer science; Multimedia; Recommender system; 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":[],"consensus_categories":[],"category_scores_codex":[0.0003702153,0.0001777489,0.0002057015,0.0003713934,0.0004085113,0.0003794459,0.0002987644,0.0001085608,0.000009570343],"category_scores_gemma":[0.0000177471,0.0001791163,0.0000905589,0.0007005832,0.00002225544,0.001376764,0.000005274547,0.0002271388,0.00001199502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002471557,"about_ca_system_score_gemma":0.0000818337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004622745,"about_ca_topic_score_gemma":0.000006134399,"domain_scores_codex":[0.998748,0.00007843222,0.0004990462,0.000244972,0.0001812291,0.0002482888],"domain_scores_gemma":[0.9991253,0.0001737509,0.0001935354,0.0002859497,0.0001617603,0.00005970444],"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":[0.00004770239,0.0003654461,0.00006465449,0.0003316762,0.0002139041,0.000002520025,0.002127296,0.04371433,0.01358661,0.004698265,0.001362597,0.933485],"study_design_scores_gemma":[0.0006170096,0.0000300031,0.00003412251,0.0002431632,0.00001676825,0.00003078747,0.0002145541,0.9857138,0.005235503,0.00002987745,0.007648279,0.0001860839],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0007979056,0.00001709915,0.9951524,0.0003139102,0.002003131,0.0003842484,0.00005213323,0.0005123947,0.0007667624],"genre_scores_gemma":[0.9051777,0.000007978235,0.09438157,0.0001737163,0.00003706268,0.00008171917,0.00002291992,0.000009006866,0.0001082905],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9419995,"threshold_uncertainty_score":0.7304149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03803041298773462,"score_gpt":0.2830329487524063,"score_spread":0.2450025357646716,"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."}}