{"id":"W2038661547","doi":"10.1145/2449396.2449401","title":"Tailoring recommendations to groups of users","year":2013,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"MovieLens; Recommender system; Computer science; Popularity; Graph; Information retrieval; Ranking (information retrieval); World Wide Web; Collaborative filtering; Theoretical computer science","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":[0.0001291747,0.00005330336,0.00008811336,0.0000942077,0.00003380825,0.00007040846,0.0004298328,0.00001956031,0.0001291837],"category_scores_gemma":[0.000008749421,0.00004399293,0.0000294191,0.0002235555,0.000004496483,0.0004731404,0.0001736445,0.00003279447,0.0001095218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001524093,"about_ca_system_score_gemma":0.000007785157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006131993,"about_ca_topic_score_gemma":0.00002085699,"domain_scores_codex":[0.9994645,0.0000207163,0.0001807886,0.0001399304,0.00007803087,0.0001160761],"domain_scores_gemma":[0.9994545,0.00003352104,0.0000404737,0.0003465317,0.00006084709,0.00006410331],"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":[3.978141e-7,0.00006069826,0.003784526,0.00001715241,0.00001982242,4.521833e-7,0.001115369,0.000004800048,0.004550749,0.5362993,0.2200436,0.2341031],"study_design_scores_gemma":[0.0008261753,0.0009983293,0.04740518,0.0003237451,0.00001103825,0.00003881964,0.001605135,0.02331579,0.2587739,0.1000566,0.565044,0.001601322],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01062456,0.000005036247,0.952193,0.008324167,0.0002454476,0.0002299796,3.303726e-7,0.0002185685,0.02815891],"genre_scores_gemma":[0.7385751,0.000002756884,0.2604327,0.0003536503,0.00001554922,0.00005517514,3.430429e-7,0.000003108663,0.0005615888],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7279506,"threshold_uncertainty_score":0.179398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03193488030126802,"score_gpt":0.2670205389209539,"score_spread":0.2350856586196859,"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."}}