{"id":"W4396674419","doi":"10.32920/25761537","title":"A Group Recommender System for Article Recommendation Using Matrix Factorization","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Recommender system; Information overload; Computer science; Matrix decomposition; Factorization; Cluster analysis; Group (periodic table); Information retrieval; The Internet; World Wide Web; Artificial intelligence; Algorithm","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":[0.002478277,0.001459115,0.002134681,0.003109069,0.001282439,0.001266786,0.001808624,0.001876898,0.005583493],"category_scores_gemma":[0.004556803,0.0006862169,0.002554119,0.003272842,0.0003267073,0.002055975,0.0007647732,0.001561027,0.005171505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008471709,"about_ca_system_score_gemma":0.001472566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03783313,"about_ca_topic_score_gemma":0.06943487,"domain_scores_codex":[0.998273,0.0004560962,0.0001255412,0.0005249901,0.0005201587,0.0001001388],"domain_scores_gemma":[0.9978026,0.0007220674,0.0001452373,0.0004016801,0.0008130273,0.0001154733],"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":[0.001153705,0.0009549943,0.006064661,0.0006110521,0.001071722,0.0003159893,0.0003622583,0.04907183,0.01860613,0.003934124,0.07189941,0.8459541],"study_design_scores_gemma":[0.0002146333,0.0004365722,0.001962373,0.00004735605,0.0002804133,0.0002662278,0.0001284905,0.9687409,0.005892906,0.005213549,0.01672532,0.00009135311],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03411544,0.003724177,0.940326,0.001261614,0.0007513053,0.0008271743,0.003264511,0.01108196,0.004647758],"genre_scores_gemma":[0.1392147,0.001157321,0.8424291,0.0004374865,0.0003370063,0.0004532014,0.004638167,0.0001958909,0.01113721],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03783313,"threshold_uncertainty_score":0.07522583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06177604068702735,"score_gpt":0.3342481418899045,"score_spread":0.2724721012028772,"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."}}