{"id":"W4230736957","doi":"10.2139/ssrn.3249069","title":"Optimal Exploration","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Computer science; Geology; Geography","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":[],"category_scores_codex":[0.008244945,0.0001153922,0.0001631215,0.0003438488,0.0005037444,0.0003213632,0.0008927343,0.0000604123,0.0004951503],"category_scores_gemma":[0.001916805,0.00008158297,0.00009682124,0.0008095843,0.0001939044,0.001344176,0.0001023106,0.001366303,0.002277562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005945205,"about_ca_system_score_gemma":0.001794624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006874339,"about_ca_topic_score_gemma":0.0002556742,"domain_scores_codex":[0.9949975,0.0002084486,0.0004494217,0.0003142441,0.001778369,0.002252034],"domain_scores_gemma":[0.9982308,0.0002501279,0.0001916628,0.0003476194,0.0008451956,0.000134551],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003214217,0.0001204209,0.0006890663,7.282682e-7,0.00009563494,0.000019051,0.001048719,0.002282096,0.001168739,0.06442946,0.005611411,0.9242132],"study_design_scores_gemma":[0.0005106068,0.000867433,0.000213855,0.000003636481,0.000004239536,0.0003940316,0.004309908,0.00510991,0.001186399,0.9551373,0.03211423,0.000148419],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06568665,0.0004481883,0.9298527,0.001836389,0.0004451386,0.00009294164,0.000001208228,0.00002988255,0.001606897],"genre_scores_gemma":[0.982486,0.000538132,0.002310311,0.00006754446,0.00178777,0.000004954279,0.000001025019,0.00001874974,0.01278551],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9275424,"threshold_uncertainty_score":0.9984993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0941705604698524,"score_gpt":0.4321125470547117,"score_spread":0.3379419865848593,"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."}}