{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005127867,0.00009538826,0.0001404081,0.00006973874,0.0001699109,0.00009012343,0.0005344419,0.00004453051,0.00002238408],"category_scores_gemma":[0.00001487649,0.00007475569,0.0000452904,0.0001818303,0.00001118929,0.0003695234,0.0001551656,0.00007607637,0.00007966513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003419963,"about_ca_system_score_gemma":0.00003617696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002059294,"about_ca_topic_score_gemma":0.000001773666,"domain_scores_codex":[0.9989581,0.000106101,0.0002442801,0.0002598698,0.0002302827,0.0002013551],"domain_scores_gemma":[0.9992118,0.00006480212,0.00006892446,0.0005223781,0.00006873505,0.00006339645],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002348606,0.0001373678,0.004392925,0.00005308864,0.00006274073,0.00004727335,0.001723354,0.00009113166,0.001083709,0.528969,0.3612334,0.1022036],"study_design_scores_gemma":[0.001098824,0.0006941206,0.003835116,0.000123619,0.000007687091,0.001856078,0.0002413134,0.6799786,0.007638963,0.008028446,0.2952122,0.001285029],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003497329,0.0001676453,0.9041616,0.0007900431,0.0007064885,0.0001957546,2.061985e-7,0.0008323615,0.08964854],"genre_scores_gemma":[0.853285,0.00002733762,0.1426991,0.0004132194,0.00008961461,0.00005305335,5.767828e-7,0.000008097479,0.003424047],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8497876,"threshold_uncertainty_score":0.3048449,"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."}}