{"id":"W2963874364","doi":"10.1017/s0269964818000256","title":"OPTIMAL SELECTION OF THE <i>k</i>-TH BEST CANDIDATE","year":2019,"lang":"en","type":"article","venue":"Probability in the Engineering and Informational Sciences","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Optimal stopping; Combinatorics; Mathematics; Selection (genetic algorithm); Stopping rule; Discrete mathematics; Statistics; Mathematical optimization; Computer science; Artificial intelligence","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":[0.003849087,0.0004990855,0.001670783,0.001025021,0.0008390161,0.002269759,0.001522964,0.001305789,0.004145177],"category_scores_gemma":[0.0173875,0.0004900967,0.0007714454,0.0009362738,0.001637291,0.002260716,0.001255196,0.001101274,0.0008052315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000946976,"about_ca_system_score_gemma":0.002536316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001206214,"about_ca_topic_score_gemma":0.001139333,"domain_scores_codex":[0.9977161,0.0008328278,0.000169171,0.0005656886,0.0003409649,0.0003752961],"domain_scores_gemma":[0.9904187,0.006430662,0.0009717184,0.0006042105,0.0008278481,0.000746767],"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":[0.003213218,0.0007512423,0.02686699,0.0009468427,0.0003666878,0.0007837248,0.0009538198,0.488295,0.0158595,0.1634867,0.01499501,0.2834813],"study_design_scores_gemma":[0.0001546356,0.0005512087,0.003866346,0.0001422249,0.0000900712,0.0003343281,0.0003433161,0.9074823,0.01042206,0.07364479,0.002897559,0.00007125687],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3274681,0.001503789,0.6502413,0.002836826,0.0001473955,0.000213555,0.0003986881,0.0004683257,0.01672199],"genre_scores_gemma":[0.8372685,0.000410557,0.1563376,0.0003213357,0.0000875098,0.0001687964,0.0004189201,0.000159869,0.004826908],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004145177,"threshold_uncertainty_score":0.02035618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01061213047116742,"score_gpt":0.2182559173910074,"score_spread":0.20764378691984,"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."}}