{"id":"W2885155228","doi":"10.1007/978-3-319-99368-3_31","title":"Exploring GTRS Based Recommender Systems with Users of Different Rating Patterns","year":2018,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Recommender system; Set (abstract data type); Preference; Data mining; Data set; Quality (philosophy); Scale (ratio); Information retrieval; Machine learning; Artificial intelligence; Statistics; Mathematics","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":[0.001828509,0.0006728522,0.0008880165,0.001000289,0.0006004047,0.002276409,0.001550582,0.001157758,0.004662424],"category_scores_gemma":[0.007938561,0.0004777787,0.001189989,0.001593888,0.0004378237,0.003169153,0.0009118405,0.001087775,0.00101277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006714682,"about_ca_system_score_gemma":0.0004818869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009893578,"about_ca_topic_score_gemma":0.01337214,"domain_scores_codex":[0.9986746,0.0006686167,0.00005474738,0.0003104331,0.000186622,0.000104914],"domain_scores_gemma":[0.995317,0.003355263,0.0001844407,0.0005145945,0.0004721388,0.0001566528],"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":[0.002965589,0.001430076,0.0499668,0.001230965,0.001665443,0.001628137,0.003404,0.4106767,0.02231453,0.07325325,0.01625112,0.4152135],"study_design_scores_gemma":[0.0000504875,0.0002207737,0.002863382,0.00002263769,0.0001164485,0.0001391892,0.00044083,0.9781773,0.0007724419,0.0151767,0.001990286,0.00002946587],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6198232,0.002165741,0.3615326,0.001689729,0.0001896633,0.0002118038,0.0007738724,0.001012121,0.0126013],"genre_scores_gemma":[0.8976119,0.0004894868,0.09493055,0.0001375972,0.00007914931,0.00006077832,0.0007178517,0.00007638519,0.005896354],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009893578,"threshold_uncertainty_score":0.01967198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07768754748696677,"score_gpt":0.2405437588336701,"score_spread":0.1628562113467034,"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."}}