{"id":"W3205724065","doi":"10.48550/arxiv.1612.01619","title":"mBART: Multidimensional Monotone BART","year":2016,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Acadia University","funders":"","keywords":"Monotonic function; Monotone polygon; Markov chain Monte Carlo; Parametric statistics; Computer science; Mathematics; Set (abstract data type); Nonparametric statistics; Bayesian probability; Multivariate statistics; Mathematical optimization; Algorithm; Applied mathematics; Econometrics; Machine learning; Artificial intelligence; Statistics","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003340878,0.0003295326,0.0004695794,0.000119532,0.0001068315,0.00002016585,0.0004073751,0.0003399308,0.0009615629],"category_scores_gemma":[0.0008097667,0.0002896512,0.0001993556,0.0001255199,0.0001905897,0.00006211673,0.0008660313,0.0004732439,0.0003499278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001290993,"about_ca_system_score_gemma":0.0001316798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002721163,"about_ca_topic_score_gemma":0.000007466865,"domain_scores_codex":[0.9982671,0.0002199738,0.0002608375,0.0007881324,0.0001089814,0.0003549783],"domain_scores_gemma":[0.9971655,0.001386358,0.0002113463,0.0008092694,0.0001992444,0.0002282976],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000489821,0.0001007373,0.0006417526,0.00008927038,0.00007876442,0.0001481313,0.00003878181,0.0001637076,0.000236347,0.9959042,0.001906494,0.0006428126],"study_design_scores_gemma":[0.0004896452,0.00003972623,0.001091604,0.0002286796,0.0001175948,0.000002941095,0.00002196588,0.0176591,0.000379019,0.9785571,0.0009875757,0.000425106],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2023431,0.00002014378,0.7840225,0.0000899403,0.0004999262,0.000307993,0.0001708064,0.0001600086,0.01238567],"genre_scores_gemma":[0.9279151,0.00005725372,0.06695945,0.00007067088,0.0001330587,0.000001879161,0.000008444576,0.00003739131,0.004816736],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.725572,"threshold_uncertainty_score":0.9999555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2023274158177658,"score_gpt":0.2700564577696237,"score_spread":0.06772904195185789,"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."}}