{"id":"W2028485238","doi":"10.1145/2623330.2623351","title":"We know what you want to buy","year":2014,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":136,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; Engineering and Physical Sciences Research Council; National Natural Science Foundation of China","keywords":"Metis; Microblogging; Recommender system; Computer science; Social media; Product (mathematics); World Wide Web; Collaborative filtering; Demographics; Matching (statistics); Internet privacy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003396826,0.0005584488,0.0004286087,0.0009830948,0.0007039248,0.001854495,0.0004038181,0.0009103905,0.08408529],"category_scores_gemma":[0.002653757,0.0002519106,0.0004725528,0.001748567,0.0002592598,0.002576032,0.0005790626,0.0009287015,0.0458103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000339799,"about_ca_system_score_gemma":0.0003914515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007992938,"about_ca_topic_score_gemma":0.01471797,"domain_scores_codex":[0.9996319,0.00004307049,0.000021579,0.00007563757,0.0001838225,0.00004397907],"domain_scores_gemma":[0.9993363,0.0002002563,0.00006416938,0.00006338207,0.0002255884,0.0001101436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004890473,0.0003546634,0.05872397,0.000883062,0.0002645448,0.001091373,0.001098774,0.0008539553,0.00689512,0.0091958,0.507103,0.4130466],"study_design_scores_gemma":[0.00006726025,0.0002315122,0.05387789,0.0003138627,0.0002412995,0.002837721,0.002762545,0.006406961,0.004010842,0.01307408,0.9160114,0.0001645043],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1799459,0.02006706,0.03387235,0.04639693,0.006220974,0.0004365442,0.05665252,0.003777046,0.6526307],"genre_scores_gemma":[0.5044215,0.01818632,0.04888904,0.01001311,0.002497501,0.0001791934,0.03237068,0.0007154337,0.3827271],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08408529,"threshold_uncertainty_score":0.2812933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0166006490435775,"score_gpt":0.249336478811887,"score_spread":0.2327358297683095,"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."}}