{"id":"W1868011046","doi":"","title":"On Identifying Good Options under Combinatorially Structured Feedback in Finite Noisy Environments","year":2015,"lang":"en","type":"article","venue":"International Conference on Machine Learning","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Oracle; Set (abstract data type); Exploit; Computer science; Quality (philosophy); Mathematical optimization; Identification (biology); Mathematics; Theoretical computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01441029,0.002380034,0.00456069,0.001743288,0.001440451,0.003476981,0.003694762,0.004311712,0.003460938],"category_scores_gemma":[0.06181924,0.00137491,0.001539405,0.002127006,0.007261812,0.008366873,0.004744851,0.003911229,0.0004893955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002346432,"about_ca_system_score_gemma":0.001930175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002485255,"about_ca_topic_score_gemma":0.001407568,"domain_scores_codex":[0.9923844,0.004328335,0.000274729,0.001307766,0.0009382515,0.0007666632],"domain_scores_gemma":[0.8807267,0.1090527,0.00480135,0.002482181,0.001428047,0.001509058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007704703,0.0001780722,0.001790898,0.0002223125,0.0001110571,0.0002445342,0.0002607998,0.8939809,0.001026631,0.08331958,0.0007289005,0.0173658],"study_design_scores_gemma":[0.00006115592,0.00009647547,0.0002747851,0.00003524992,0.0000191434,0.00004728144,0.00004241018,0.9000157,0.0005797727,0.09864058,0.0001523201,0.00003513403],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07247603,0.0006217445,0.922708,0.001001103,0.00003763039,0.0001629698,0.0002464949,0.0003404849,0.002405511],"genre_scores_gemma":[0.8312742,0.0007994482,0.1616574,0.0005667134,0.0001858773,0.0005910154,0.0006009268,0.0001801086,0.004144302],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01441029,"threshold_uncertainty_score":0.07620978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2028115132751566,"score_gpt":0.4445514399849025,"score_spread":0.2417399267097459,"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."}}