{"id":"W3012881846","doi":"10.1145/3366423.3380130","title":"Off-policy Learning in Two-stage Recommender Systems","year":2020,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Recommender system; Computer science; Scalability; Latency (audio); Ranking (information retrieval); Matching (statistics); Stage (stratigraphy); Information retrieval; Machine learning; Artificial intelligence; Database; Telecommunications","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":[0.0003981757,0.0001431792,0.0002428203,0.0001529636,0.00005979005,0.0002543298,0.000669226,0.00004536764,0.00002428513],"category_scores_gemma":[0.00004769574,0.0001243109,0.00005112291,0.0006171317,0.000009153487,0.0004222641,0.0003127934,0.0002615859,0.00007166939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006979819,"about_ca_system_score_gemma":0.00006851245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001830573,"about_ca_topic_score_gemma":0.0000537621,"domain_scores_codex":[0.9985923,0.0001985746,0.0003528366,0.0003824928,0.0001710028,0.0003028492],"domain_scores_gemma":[0.9993675,0.00006762167,0.00009400201,0.0003033151,0.00002997189,0.0001375334],"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":[0.000006578501,0.00007804838,0.01546131,0.0001562661,0.00003403141,0.00006658934,0.004356105,0.00162101,0.0006666621,0.8226266,0.03481133,0.1201155],"study_design_scores_gemma":[0.0005632538,0.0001290413,0.000429588,0.00004907978,0.000001083601,0.00001315604,0.0004446817,0.3680133,0.0008000484,0.0004160802,0.628783,0.0003577205],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001775489,0.0002461088,0.831698,0.02377008,0.0002863325,0.000374432,8.236672e-7,0.00139875,0.14045],"genre_scores_gemma":[0.9870675,0.0000424465,0.008157125,0.002269087,0.0001831133,0.00003741408,0.000001251993,0.0000141823,0.002227847],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.985292,"threshold_uncertainty_score":0.5069252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04758359732466737,"score_gpt":0.3093846935768848,"score_spread":0.2618010962522174,"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."}}