{"id":"W2996286957","doi":"10.1287/opre.2021.2114","title":"Optimal Sequential Multiclass Diagnosis","year":2021,"lang":"en","type":"preprint","venue":"Operations Research","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"University of Toronto; University of Illinois at Urbana-Champaign; Queen's University","keywords":"Curse of dimensionality; Dimension (graph theory); Computer science; Heuristic; Univariate; Matrix (chemical analysis); Class (philosophy); Statistic; Exponential family; Rank (graph theory); Mathematical optimization; Mathematics; Artificial intelligence; Multivariate statistics; Machine learning; Statistics; Combinatorics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003281122,0.00126463,0.002530087,0.001101168,0.0009009805,0.001529402,0.001639383,0.002220781,0.003758249],"category_scores_gemma":[0.0139638,0.0009237301,0.0009540725,0.001182488,0.001734342,0.002241557,0.002294064,0.002596802,0.0005338768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001964775,"about_ca_system_score_gemma":0.003899815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006493847,"about_ca_topic_score_gemma":0.004809196,"domain_scores_codex":[0.9975339,0.0007628131,0.0001457512,0.000764607,0.0004547708,0.0003381422],"domain_scores_gemma":[0.9936334,0.004593595,0.0005221277,0.0003577631,0.0006363001,0.0002567265],"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":[0.00045153,0.0001832035,0.002659689,0.0002352904,0.0001146299,0.0002087749,0.000185499,0.7448432,0.001555481,0.07993202,0.008492883,0.1611377],"study_design_scores_gemma":[0.00002607069,0.00004431992,0.000149799,0.00001466534,0.00001153653,0.00003398489,0.00001724075,0.9493517,0.0006669535,0.04888726,0.0007853062,0.00001116462],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01442758,0.0004420525,0.9804827,0.00120474,0.000140572,0.0001036898,0.0001757788,0.0004406316,0.002582278],"genre_scores_gemma":[0.6454049,0.00054251,0.3465426,0.0007234069,0.0002690942,0.0003031236,0.0005884657,0.0001171491,0.005508788],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006493847,"threshold_uncertainty_score":0.0173524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5527928944872087,"score_gpt":0.6121143874927769,"score_spread":0.05932149300556822,"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."}}