{"id":"W4386010134","doi":"10.21203/rs.3.rs-3263186/v1","title":"Uncertainty-Aware Graph Neural Network for Semi-Supervised Diversified Recommendation","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Machine learning; Recommender system; Artificial intelligence; Generalization; Graph; Selection (genetic algorithm); Baseline (sea); Set (abstract data type); Supervised learning; Data mining; Artificial neural network; Data science; Theoretical computer science","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":[0.001297941,0.001150818,0.002315753,0.0013277,0.0006027915,0.0010804,0.002419262,0.00247243,0.00248735],"category_scores_gemma":[0.00613346,0.000777122,0.000851349,0.001966207,0.0008239701,0.002590853,0.001315749,0.002282679,0.0008195107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001175115,"about_ca_system_score_gemma":0.001207891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01306385,"about_ca_topic_score_gemma":0.02077297,"domain_scores_codex":[0.9991604,0.0002306826,0.00004871738,0.0002803468,0.0001913411,0.0000886212],"domain_scores_gemma":[0.9973852,0.001518856,0.0002017578,0.0004056886,0.0003879875,0.0001005344],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004298093,0.0002769794,0.001641398,0.0001650015,0.0002272621,0.0001070005,0.00008034494,0.7225094,0.002915629,0.008856346,0.007999699,0.2547911],"study_design_scores_gemma":[0.000005128443,0.00001119968,0.00006711636,0.00000329876,0.000007194065,0.000008705832,0.000002560823,0.9963422,0.0001885347,0.003264947,0.00009546903,0.000003412203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0379534,0.001307182,0.9563726,0.0005560695,0.0001042068,0.0000745675,0.0004532249,0.00146689,0.001711817],"genre_scores_gemma":[0.8058124,0.0006860183,0.1841236,0.0004506984,0.0002428789,0.0001487306,0.001511214,0.0002239279,0.006800656],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01306385,"threshold_uncertainty_score":0.02597564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1459529906068883,"score_gpt":0.3951745048275275,"score_spread":0.2492215142206392,"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."}}