{"id":"W2962856402","doi":"10.1093/ej/uez043","title":"Learning While Experimenting","year":2019,"lang":"en","type":"article","venue":"The Economic Journal","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Toronto","funders":"","keywords":"Pessimism; State (computer science); Computer science; Epistemology","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004928112,0.00007714443,0.0001605417,0.0001285821,0.0004052153,0.0005909482,0.0009787154,0.00002638863,0.01037705],"category_scores_gemma":[0.0003669422,0.00004455437,0.00009910657,0.00009224869,0.00005866191,0.0005199966,0.0002093401,0.0005660022,0.01380093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001908759,"about_ca_system_score_gemma":0.0001255099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004862438,"about_ca_topic_score_gemma":0.000001555827,"domain_scores_codex":[0.9984022,0.0002280339,0.0004226703,0.0001990265,0.0004260319,0.0003219722],"domain_scores_gemma":[0.9983382,0.0009114199,0.0002740782,0.0003225175,0.00006500317,0.00008877888],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001730125,0.00003946103,0.04586031,0.000003597012,0.0001103609,0.00003572672,0.01055324,0.5602634,0.004677853,0.001789418,0.02822982,0.3482638],"study_design_scores_gemma":[0.003715826,0.0005304133,0.01380947,0.00004822638,0.00001158014,0.001481663,0.04553823,0.2462498,0.008571652,0.09669404,0.5826186,0.0007305738],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9759886,0.000213344,0.002697263,0.0007422893,0.00112065,0.00008840105,6.544561e-7,0.00001420002,0.01913455],"genre_scores_gemma":[0.9788173,0.00002518792,0.0002564045,0.00005318561,0.0005655125,0.000001714532,1.70786e-7,0.00001141138,0.02026909],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5543888,"threshold_uncertainty_score":0.9905276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09921364006409483,"score_gpt":0.4137674019392119,"score_spread":0.3145537618751171,"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."}}