{"id":"W2101101192","doi":"","title":"Collaborative Ranking With 17 Parameters","year":2012,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Ranking (information retrieval); Hyperparameter; Retraining; Collaborative filtering; Computer science; Machine learning; Ranking SVM; Domain (mathematical analysis); Set (abstract data type); Artificial intelligence; Perspective (graphical); Learning to rank; Recommender system; Information retrieval; Data mining; 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":[0.003876914,0.00214603,0.002486171,0.001458344,0.0009996869,0.00214699,0.003608138,0.003566786,0.01300763],"category_scores_gemma":[0.01917907,0.001093526,0.001980493,0.002558854,0.001061901,0.003933165,0.00196051,0.003350003,0.008320699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00159973,"about_ca_system_score_gemma":0.002593984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007219348,"about_ca_topic_score_gemma":0.01090363,"domain_scores_codex":[0.9966295,0.001459962,0.0002424144,0.0007115789,0.0006737004,0.0002828358],"domain_scores_gemma":[0.9929092,0.003646711,0.0003235973,0.002109762,0.0008502034,0.0001605229],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00060592,0.0005293352,0.003669652,0.0003710202,0.000358072,0.0002148811,0.0001358476,0.5942269,0.003185512,0.0176793,0.01551399,0.3635097],"study_design_scores_gemma":[0.0002535566,0.000152801,0.0008585698,0.00004360809,0.0001008574,0.0002096109,0.00004090113,0.9674833,0.00285619,0.0224901,0.005435314,0.00007503258],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04522004,0.001581827,0.9311745,0.0008243742,0.0002388683,0.0005140523,0.002518191,0.005698631,0.01222965],"genre_scores_gemma":[0.5254719,0.0005849321,0.4557497,0.000479448,0.0002329556,0.001279073,0.003341045,0.0004717336,0.01238914],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01300763,"threshold_uncertainty_score":0.04351491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01579375357659719,"score_gpt":0.2462145974474512,"score_spread":0.230420843870854,"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."}}