{"id":"W2169020911","doi":"10.1109/axmedis.2008.21","title":"Evaluating Recommender Systems","year":2008,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"MovieLens; Recommender system; Computer science; Collaborative filtering; Information overload; Information retrieval; 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":[0.01574228,0.001799757,0.002615457,0.005179379,0.0009654661,0.003732417,0.001503584,0.002214332,0.003941505],"category_scores_gemma":[0.0928616,0.0003978795,0.001246281,0.005110048,0.0005726047,0.003260118,0.001157706,0.001163312,0.001793602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00159866,"about_ca_system_score_gemma":0.001242661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006972027,"about_ca_topic_score_gemma":0.006914589,"domain_scores_codex":[0.9726515,0.01325892,0.002002306,0.002994801,0.008572137,0.0005203182],"domain_scores_gemma":[0.9441466,0.03738226,0.002925189,0.004814376,0.009922276,0.0008092771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000986766,0.0006093846,0.06483015,0.002010712,0.002530295,0.0001913176,0.0003612242,0.1871338,0.00306192,0.02172333,0.0222401,0.694321],"study_design_scores_gemma":[0.0003628668,0.002765137,0.04387573,0.0006401245,0.001324796,0.0007728823,0.0007986823,0.8602116,0.007168716,0.03903807,0.04275203,0.0002894872],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2873849,0.02892984,0.6152236,0.002719865,0.001501726,0.001771289,0.009170139,0.002382809,0.05091582],"genre_scores_gemma":[0.7301408,0.005135391,0.2489507,0.0005074724,0.0005926586,0.0005335467,0.009055786,0.0001573366,0.004926267],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01574228,"threshold_uncertainty_score":0.08325416,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2048137453607044,"score_gpt":0.3611611224585276,"score_spread":0.1563473770978232,"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."}}