{"id":"W3204874277","doi":"10.48550/arxiv.2109.14733","title":"Batched Bandits with Crowd Externalities","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Microsoft (Canada)","funders":"","keywords":"Externality; Computer science; Economics; Microeconomics","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00118436,0.0004604486,0.0007486134,0.0006172873,0.0002771772,0.0007493423,0.002573445,0.0003578539,0.002057795],"category_scores_gemma":[0.0008124289,0.0003931167,0.0003184681,0.001506359,0.0005282218,0.0007183997,0.002526554,0.001149878,0.0003471009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000313834,"about_ca_system_score_gemma":0.0007160879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002712029,"about_ca_topic_score_gemma":0.0004183424,"domain_scores_codex":[0.9953271,0.000497341,0.0004466514,0.002056033,0.00100956,0.0006633629],"domain_scores_gemma":[0.9945298,0.001166603,0.0004288245,0.002206658,0.00129791,0.0003702193],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006610124,0.0003222139,0.02903945,0.0001214153,0.0004795135,0.01043561,0.001822124,0.9448555,0.0000960195,0.005000719,0.002559537,0.004606859],"study_design_scores_gemma":[0.007726545,0.0008153214,0.061833,0.001422486,0.0004933031,0.0002348673,0.03155563,0.3797205,0.00578316,0.4825782,0.02213284,0.00570417],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5806645,0.000198526,0.4149619,0.0001225222,0.0005008649,0.0002957817,0.00006187363,0.0001089865,0.003085047],"genre_scores_gemma":[0.9573222,0.0001780525,0.001108692,0.00005798047,0.0001930242,0.000002282832,0.00002997207,0.00004090098,0.04106683],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.565135,"threshold_uncertainty_score":0.9998521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2814954423330207,"score_gpt":0.2986513873188594,"score_spread":0.01715594498583872,"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."}}