{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001137853,0.0009435775,0.00150485,0.0009601791,0.0008885958,0.001183372,0.002760941,0.001346315,0.002732003],"category_scores_gemma":[0.002977629,0.0004497011,0.0006960001,0.001610756,0.0004333507,0.002269328,0.001323656,0.001094648,0.001615678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005677749,"about_ca_system_score_gemma":0.0006324798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00386147,"about_ca_topic_score_gemma":0.005096732,"domain_scores_codex":[0.9987382,0.0002036132,0.00009046488,0.0004216962,0.0004515521,0.00009439445],"domain_scores_gemma":[0.9982917,0.0004109091,0.0001526146,0.000640716,0.0003983769,0.0001056971],"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":[0.001004984,0.000422679,0.003346944,0.000445586,0.0004154514,0.0008378915,0.0003140694,0.1858783,0.06184562,0.0264503,0.01357675,0.7054614],"study_design_scores_gemma":[0.0001003043,0.0001995938,0.0005979159,0.00001346814,0.00008054579,0.0004338823,0.00005701793,0.9720229,0.01162011,0.006577424,0.008240745,0.00005615537],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01851837,0.000886545,0.9751388,0.0002183493,0.0001169354,0.0001306783,0.000189892,0.002380374,0.00242002],"genre_scores_gemma":[0.5086401,0.0009007382,0.4791996,0.0004006204,0.0003526983,0.0002644822,0.0007415498,0.0001091332,0.009391071],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00386147,"threshold_uncertainty_score":0.009139478,"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."}}