{"id":"W301125580","doi":"10.1007/978-3-642-40261-6_44","title":"On Achieving Near-Optimal “Anti-Bayesian” Order Statistics-Based Classification for Asymmetric Exponential Distributions","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Exponential family; Order statistic; Bayesian probability; Natural exponential family; Computer science; Exponential function; Exponential distribution; Beta distribution; Bayes' theorem; Gamma distribution; Probability distribution; Bayesian statistics; Statistics; Mathematics; Applied mathematics; Bayesian inference; Mathematical analysis","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":[0.006068787,0.001961435,0.003267921,0.001776654,0.001465725,0.003117035,0.003736746,0.003215045,0.003085231],"category_scores_gemma":[0.02006704,0.001176006,0.001728585,0.002071584,0.002656893,0.005541271,0.005146215,0.004868466,0.001858665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002063617,"about_ca_system_score_gemma":0.003566946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003623365,"about_ca_topic_score_gemma":0.005777945,"domain_scores_codex":[0.9942941,0.002362385,0.0003672237,0.0007409376,0.001673054,0.0005623633],"domain_scores_gemma":[0.9856445,0.0103258,0.0006216271,0.00177579,0.001168223,0.0004640919],"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":[0.0009098819,0.0004778773,0.002500762,0.0003980763,0.0001992652,0.0001660195,0.0005007458,0.3100665,0.00943618,0.2605827,0.01768626,0.3970756],"study_design_scores_gemma":[0.00002813673,0.00005447788,0.0002021597,0.00002049364,0.00001664441,0.00005990823,0.00002962595,0.8718752,0.00155796,0.1252387,0.0008954132,0.00002115238],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02016706,0.0005341306,0.9744465,0.0006354073,0.00008026653,0.00006058582,0.0001285859,0.000910468,0.003036952],"genre_scores_gemma":[0.3748858,0.0009657405,0.6130855,0.001175882,0.000441312,0.0002557604,0.001363324,0.000442671,0.007384115],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006068787,"threshold_uncertainty_score":0.03209519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0199869348379255,"score_gpt":0.2721561320991968,"score_spread":0.2521691972612712,"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."}}