{"id":"W2020631728","doi":"10.1145/1639714.1639717","title":"Collaborative prediction and ranking with non-random missing data","year":2009,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":318,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of British Columbia","funders":"","keywords":"Missing data; Collaborative filtering; Recommender system; Computer science; Ranking (information retrieval); Data mining; Process (computing); Random forest; Information retrieval; Machine learning; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03979848,0.001883617,0.005569156,0.002277832,0.002204681,0.003671855,0.006545519,0.003950701,0.003469129],"category_scores_gemma":[0.150955,0.002224829,0.002477256,0.004332002,0.003193218,0.008264224,0.003610824,0.004394324,0.001194173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001826199,"about_ca_system_score_gemma":0.001972517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007011278,"about_ca_topic_score_gemma":0.005530946,"domain_scores_codex":[0.9639707,0.0213507,0.001731365,0.006645649,0.004685344,0.001616188],"domain_scores_gemma":[0.7246528,0.2165084,0.01437381,0.03459425,0.008230238,0.001640394],"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":[0.0009789977,0.0004003308,0.01540797,0.00112294,0.001367117,0.001110009,0.001041426,0.6930459,0.001058774,0.1496564,0.004286205,0.1305239],"study_design_scores_gemma":[0.00007927831,0.0001670413,0.001723197,0.00006269127,0.0001426726,0.000243903,0.00008885399,0.8811983,0.0005494827,0.1146159,0.001060668,0.00006795651],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02772782,0.001235293,0.968393,0.0007744033,0.0001048451,0.00009481259,0.0003407784,0.0002824266,0.00104653],"genre_scores_gemma":[0.7844899,0.001544575,0.2079974,0.0004033444,0.0006115127,0.0004202218,0.001242928,0.0001084601,0.003181641],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03979848,"threshold_uncertainty_score":0.210477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0173776992655103,"score_gpt":0.26040023312817,"score_spread":0.2430225338626597,"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."}}