{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002806686,0.00008256056,0.000113801,0.00006515931,0.00004744028,0.0004332706,0.000637992,0.00003385697,0.00002770783],"category_scores_gemma":[0.000007840476,0.00005977538,0.00003791487,0.0001479632,0.000005103871,0.0005763776,0.0002517071,0.00004405202,0.0002892569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001562535,"about_ca_system_score_gemma":0.00000963307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007960209,"about_ca_topic_score_gemma":0.00002631969,"domain_scores_codex":[0.9992593,0.00004009709,0.0001373227,0.0002505349,0.000131132,0.0001816092],"domain_scores_gemma":[0.9992446,0.00003003887,0.00002520113,0.0005666378,0.00003110949,0.0001024631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[3.061209e-7,0.00001398635,0.00004458465,0.000005306053,0.000002874506,9.793373e-7,0.0004455163,6.818067e-7,0.000222444,0.1785177,0.04396924,0.7767763],"study_design_scores_gemma":[0.00005336035,0.000100347,0.00007651252,0.00006131032,6.216563e-7,0.000008959448,0.00005981323,0.004847866,0.01015841,0.008451302,0.9760479,0.000133597],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003269467,0.0001683979,0.9499037,0.02219905,0.0006397151,0.000120912,8.988268e-8,0.0004556786,0.0261855],"genre_scores_gemma":[0.7122482,0.0003460807,0.2701708,0.004589582,0.0002410684,0.00005312475,4.71494e-7,0.00001418165,0.01233645],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9320787,"threshold_uncertainty_score":0.4178039,"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."}}