{"id":"W2043281479","doi":"10.1145/2339530.2339731","title":"RecMax","year":2012,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Recommender system; MovieLens; Heuristics; Computer science; Collaborative filtering; Product (mathematics); Set (abstract data type); Joke; Machine learning; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001737085,0.00002963263,0.00003640373,0.0000205367,0.00002133934,0.00003226043,0.0002274016,0.00001611979,0.00003269206],"category_scores_gemma":[0.000002435635,0.00002128006,0.00001639925,0.00006698253,0.000002520774,0.0004011804,0.00007643552,0.00002218028,0.0001276949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006873315,"about_ca_system_score_gemma":0.000003183747,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002659878,"about_ca_topic_score_gemma":7.785629e-7,"domain_scores_codex":[0.9996994,0.00001390293,0.0000551825,0.00005584761,0.00005148061,0.0001241667],"domain_scores_gemma":[0.9996966,0.00001057032,0.00001229826,0.0002257287,0.000008105741,0.00004669595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[5.76226e-8,0.0000166906,0.004029703,0.00000146798,0.000001962704,2.349824e-7,0.000151409,1.008981e-8,0.0001156668,0.8545808,0.05915688,0.08194517],"study_design_scores_gemma":[0.00004404715,0.00001904855,0.004711465,0.000003792521,4.971531e-7,0.00002764466,0.00001133811,0.0004636875,0.01613405,0.00555407,0.9729155,0.0001148242],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003486302,0.00007171702,0.7464221,0.0005684699,0.00028628,0.00002819981,2.614775e-8,0.0003069813,0.2519676],"genre_scores_gemma":[0.8576245,0.000002992503,0.1400376,0.0003764142,0.00006956657,0.000005913208,6.816686e-8,0.000001602779,0.001881383],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9137586,"threshold_uncertainty_score":0.1641302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02708492850755454,"score_gpt":0.256719513032832,"score_spread":0.2296345845252774,"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."}}