{"id":"W1551228660","doi":"10.48550/arxiv.1212.2442","title":"Active Collaborative Filtering","year":2012,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Collaborative filtering; Computer science; Computation; Focus (optics); Recommender system; Quantization (signal processing); Online and offline; Quality (philosophy); Vector quantization; Theoretical computer science; Machine learning; Artificial intelligence; Algorithm","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002016555,0.0003017881,0.0003473368,0.0001998332,0.0001355806,0.0001509084,0.001570632,0.0002800984,0.00002850538],"category_scores_gemma":[0.00001077688,0.0003323466,0.0001458807,0.0004927287,0.00004922515,0.0006912021,0.002519314,0.0004784509,0.00006364452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002613708,"about_ca_system_score_gemma":0.0001491667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001602553,"about_ca_topic_score_gemma":0.0000253684,"domain_scores_codex":[0.9984248,0.0001755408,0.0001688078,0.0007944019,0.00007395921,0.0003625147],"domain_scores_gemma":[0.9981841,0.00006992664,0.0002871963,0.001113168,0.0001806025,0.0001649784],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004627545,0.0002753902,0.002140339,0.0002405056,0.0005106764,0.0004124191,0.004528731,0.00430866,0.0004286621,0.9684002,0.006272557,0.01243553],"study_design_scores_gemma":[0.00323262,0.0006074921,0.01221291,0.001892225,0.0004657623,0.00009883412,0.002612475,0.371421,0.05757127,0.4017916,0.1394873,0.008606528],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02870287,0.000109136,0.9448902,0.0001117125,0.001145042,0.0004431788,0.00002909186,0.0005995063,0.02396927],"genre_scores_gemma":[0.9925734,0.0001111034,0.006174431,0.00005690502,0.0001220633,0.000003832834,0.000008144641,0.00001639099,0.0009337594],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9638705,"threshold_uncertainty_score":0.9999129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08900886807113924,"score_gpt":0.1995778527243885,"score_spread":0.1105689846532493,"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."}}