{"id":"W3155932503","doi":"10.4018/ijiit.2021040102","title":"Evaluating Recommender Systems","year":2021,"lang":"en","type":"article","venue":"International Journal of Intelligent Information Technologies","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Recommender system; Consistency (knowledge bases); Variety (cybernetics); Process (computing); Face (sociological concept); Information retrieval; Data science; Artificial intelligence","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":[0.0008239573,0.0001146716,0.0001916978,0.0005156815,0.00004985343,0.0006315042,0.001557726,0.0001070227,0.00001646423],"category_scores_gemma":[0.0006962224,0.000094107,0.0001248849,0.0002697077,0.00002330304,0.002687786,0.0004035974,0.0002547806,0.00003563765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001869378,"about_ca_system_score_gemma":0.00014632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008132024,"about_ca_topic_score_gemma":5.756372e-7,"domain_scores_codex":[0.9979594,0.00005693276,0.001045567,0.00009129511,0.000709267,0.000137592],"domain_scores_gemma":[0.996139,0.0001171958,0.000900662,0.0003031084,0.002511787,0.00002825832],"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":[0.000008998509,0.00005350343,0.0001717532,0.00002003743,0.0001868131,0.00003000438,0.0005832062,0.0006741919,0.0003259247,0.169392,0.0184993,0.8100542],"study_design_scores_gemma":[0.0006062647,0.0003536632,0.00008506965,0.0004798813,0.00001413408,0.002755985,0.00817654,0.03659691,0.2374201,0.03525006,0.6778625,0.0003989449],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00150269,0.0006697682,0.978201,0.01198839,0.004065781,0.00008618336,0.00000324514,0.0003627985,0.003120115],"genre_scores_gemma":[0.8630111,0.001023287,0.135074,0.000574169,0.0001113773,0.00001706228,0.000008962635,0.000006663097,0.0001733582],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8615084,"threshold_uncertainty_score":0.6089609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06513641393096989,"score_gpt":0.3546792321351041,"score_spread":0.2895428182041342,"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."}}